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<p>Road traffic noise is a significant environmental problem and a major source of environmental impact, adversely affecting public health and quality of life in urban areas. This study was conducted to assess exposure to road traffic noise and related health risks in Niğde city center, Türkiye, and to evaluate the effectiveness of traffic management-based reduction scenarios. Strategic noise mapping was performed by integrating traffic volume, vehicle speed, road geometry, building characteristics, land use, and ground absorption data obtained from NDVI using the GIS-based SoundPLAN model. Noise levels were assessed using the Lday, Lnight, and Lden indicators and compared with internationally recognized environmental noise guideline values reported by the WHO, the European Commission, and the European Environment Agency. The results indicated that 40.68% of the population (14,600 people) was exposed to ≥ 45&#xa0;dB(A) Lnight levels associated with sleep disturbance effects, while 11.42% of the population was exposed to ≥ 70&#xa0;dB(A) Lden levels representing critical health risk conditions according to WHO-based environmental noise assessments. The findings further showed that high noise exposure was concentrated particularly along the main urban transportation corridor, Ataturk Boulevard. Scenario-based interventions, including speed reduction and traffic diversion to alternative routes, significantly reduced high-risk noise exposure. Following the scenario implementation, the population exposed to ≥ 45&#xa0;dB(A) Lnight decreased by approximately 7%, while the population exposed to ≥ 70&#xa0;dB(A) Lden decreased from 11.42% to 1.39%. The findings demonstrate that traffic management strategies can effectively reduce harmful environmental noise exposure and support the protection of sensitive urban land uses. This study highlights the value of scenario-based strategic noise mapping as a decision-support tool for integrating environmental noise control into urban planning and public health policies in medium-sized cities.</p>

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Road traffic noise, population exposure levels, and health thresholds: a scenario-based noise control approach

  • 期刊论文

  • 发表日期：

    2026年7月18日

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  • Barış Kahveci,
  • Nuriye Ebru Yıldız

摘要

Road traffic noise is a significant environmental problem and a major source of environmental impact, adversely affecting public health and quality of life in urban areas. This study was conducted to assess exposure to road traffic noise and related health risks in Niğde city center, Türkiye, and to evaluate the effectiveness of traffic management-based reduction scenarios. Strategic noise mapping was performed by integrating traffic volume, vehicle speed, road geometry, building characteristics, land use, and ground absorption data obtained from NDVI using the GIS-based SoundPLAN model. Noise levels were assessed using the Lday, Lnight, and Lden indicators and compared with internationally recognized environmental noise guideline values reported by the WHO, the European Commission, and the European Environment Agency. The results indicated that 40.68% of the population (14,600 people) was exposed to ≥ 45 dB(A) Lnight levels associated with sleep disturbance effects, while 11.42% of the population was exposed to ≥ 70 dB(A) Lden levels representing critical health risk conditions according to WHO-based environmental noise assessments. The findings further showed that high noise exposure was concentrated particularly along the main urban transportation corridor, Ataturk Boulevard. Scenario-based interventions, including speed reduction and traffic diversion to alternative routes, significantly reduced high-risk noise exposure. Following the scenario implementation, the population exposed to ≥ 45 dB(A) Lnight decreased by approximately 7%, while the population exposed to ≥ 70 dB(A) Lden decreased from 11.42% to 1.39%. The findings demonstrate that traffic management strategies can effectively reduce harmful environmental noise exposure and support the protection of sensitive urban land uses. This study highlights the value of scenario-based strategic noise mapping as a decision-support tool for integrating environmental noise control into urban planning and public health policies in medium-sized cities.