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法国风力涡轮机噪声暴露量的量化。

Quantification of Sound Exposure from Wind Turbines in France.

机构信息

UMRAE, Cerema, Univ Gustave Eiffel, IFSTTAR, F-67035 Strasbourg, France.

Umrestte UMR T9405, Univ Lyon, Univ Gustave Eiffel, IFSTTAR, Univ Lyon 1, F-69675 Bron, France.

出版信息

Int J Environ Res Public Health. 2021 Dec 21;19(1):23. doi: 10.3390/ijerph19010023.

DOI:10.3390/ijerph19010023
PMID:35010281
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8751230/
Abstract

The WHO guidelines on environmental noise highlight that evidence on the health effects of wind turbine sound levels is either non-existent or of poor quality. In this context, a feasibility study was conducted in France in 2017. The objective was to suggest a methodology for calculating wind turbine sound levels in order to quantify the number of windfarms' residents exposed to this sound. Based on a literature review, the Harmonoise model was selected for sound exposure calculation. It was validated by quantifying its uncertainties, and finally used to estimate the population exposed to wind turbine sound in metropolitan France. Compared to other environmental noise sources (e.g., transportation), sound exposure is very moderate, with more than 80% of the exposed people exposed to sound levels below 40 dBA. The total number of people exposed to more than 30 dBA is about 686,000 and 722,000 people for typical daytime and night-time meteorological conditions respectively, i.e., about 1% of the French population in 2017. These results represent the first ever assessment of sound exposure from wind turbines at the scale of the entire metropolitan France.

摘要

世界卫生组织关于环境噪声的指南强调，有关风力涡轮机噪声水平对健康影响的证据要么不存在，要么质量较差。在这种情况下，法国于 2017 年进行了一项可行性研究。目的是提出一种计算风力涡轮机噪声水平的方法，以量化暴露于这种噪声的风电场居民人数。基于文献综述，选择了 Harmonoise 模型进行声暴露计算。通过量化其不确定性对其进行了验证，最后用于估算法国大都市地区受风力涡轮机噪声影响的人口。与其他环境噪声源（如交通）相比，声暴露水平非常适中，超过 80%的受影响人群暴露于 40 dBA 以下的噪声水平。典型的白天和夜间气象条件下，超过 30 dBA 的暴露总人数分别约为 686,000 人和 722,000 人，即 2017 年约占法国人口的 1%。这些结果代表了首次对整个法国大都市地区风力涡轮机噪声暴露情况进行评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/03ef497b4973/ijerph-19-00023-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/1b466d1c8b82/ijerph-19-00023-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/8fff8fe3a8fb/ijerph-19-00023-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/81fe0da08e23/ijerph-19-00023-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/e3c6f40ed266/ijerph-19-00023-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/22ad387cb33f/ijerph-19-00023-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/88ffd1ba5ab7/ijerph-19-00023-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/ca85ddfc5423/ijerph-19-00023-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/b66afe837706/ijerph-19-00023-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/ec9713c89fec/ijerph-19-00023-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/03ef497b4973/ijerph-19-00023-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/1b466d1c8b82/ijerph-19-00023-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/8fff8fe3a8fb/ijerph-19-00023-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/81fe0da08e23/ijerph-19-00023-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/e3c6f40ed266/ijerph-19-00023-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/22ad387cb33f/ijerph-19-00023-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/88ffd1ba5ab7/ijerph-19-00023-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/ca85ddfc5423/ijerph-19-00023-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/b66afe837706/ijerph-19-00023-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/ec9713c89fec/ijerph-19-00023-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f5c/8751230/03ef497b4973/ijerph-19-00023-g010.jpg

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本文引用的文献

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Health Effects Related to Wind Turbine Sound: An Update.与风力涡轮机噪声相关的健康影响：最新研究进展。
Int J Environ Res Public Health. 2021 Aug 30;18(17):9133. doi: 10.3390/ijerph18179133.
2
Environmental parameters sensitivity analysis for the modeling of wind turbine noise in downwind conditions.下风条件下风力涡轮机噪声建模的环境参数敏感性分析
J Acoust Soc Am. 2020 Dec;148(6):3623. doi: 10.1121/10.0002872.
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Extended source models for wind turbine noise propagation.风力涡轮机噪声传播的扩展源模型。
J Acoust Soc Am. 2019 Mar;145(3):1363. doi: 10.1121/1.5093307.
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J Acoust Soc Am. 2017 Nov;142(5):3297. doi: 10.1121/1.5012747.
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Wind turbine sound pressure level calculations at dwellings.住宅处风力涡轮机声压级计算
J Acoust Soc Am. 2016 Mar;139(3):1436-42. doi: 10.1121/1.4942404.
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Impact of wind turbine noise in the Netherlands.荷兰风力涡轮机噪音的影响。
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Low-frequency noise from large wind turbines.大型风力涡轮机的低频噪声。
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