Jiangsu Key Laboratory for Chemistry of Low-Dimensonal Material, Jiangsu Collaborative Innovation Center of Regional Modern Agriculture & Environmental Protection, School of Chemistry and Chemical Engineering, Huaiyin Normal University, Huaian, 223300, China.
Department of Decision Sciences, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China.
Environ Res. 2020 Jun;185:109437. doi: 10.1016/j.envres.2020.109437. Epub 2020 Mar 30.
This study developed a prediction model for estimating urban inland waterway traffic noise emission level. The model based on the Scandinavian Nord 2000 method, which was modified by adding two categories of traffic flow, comprising light and heavy vessels, as well as vessel average speed to the calculating equations. Meanwhile, the influences of the water surface and embankment were also considered in the established model. Model verification was conducted using the data surveyed at the 30 sampling points of Danjinlicaohe Channel in Jiangsu Province of China. A high correlation was found between the predicted and measured noise values L (Pearson correlation coefficient = 0.949, p < 0.01). And the mean difference between the predicted and measured noise values was 0.16 ± 1.28 dBA. The results showed that the proposed model had higher accuracy than the unmodified Nord 2000 method and can be applied for predicting vessel noise exposure level on inland waterway of China.
本研究开发了一种预测模型，用于估算城市内河水道交通噪声排放水平。该模型基于斯堪的纳维亚 Nord 2000 方法，通过在计算公式中添加两类交通流量（轻型和重型船舶以及船舶平均速度）以及水面和堤岸的影响，对其进行了修正。利用中国江苏省大津里槽河 30 个采样点的测量数据对模型进行了验证。预测值和实测值之间的相关性较高（皮尔逊相关系数为 0.949，p<0.01）。预测值和实测值之间的平均差值为 0.16±1.28 dBA。结果表明，与未经修正的 Nord 2000 方法相比，所提出的模型具有更高的准确性，可用于预测中国内河水道的船舶噪声暴露水平。
