Civil Engineering Department, Malaviya National Institute of Technology JLN Marg, Jaipur, Rajasthan, 302017, India.
Environ Monit Assess. 2011 Jan;172(1-4):113-20. doi: 10.1007/s10661-010-1320-z. Epub 2010 Feb 6.
The main objective of the present study was to develop an empirical noise prediction model for the evaluation of equivalent noise level (Leq) in terms of equivalent traffic density number under heterogeneous traffic flow conditions. Ten commercial road networks are selected for monitoring and modeling. A new factor, i.e., equivalent number of light vehicles (EqLv) and for heavy vehicles (EqHv), has been used for evaluating the equivalent traffic density for each class of vehicles, and correlation graphs are plotted between equivalent traffic density with respect to EqLv and EqHv and observed equivalent noise level [Leq(o)] for the calculation of equivalent noise levels in terms of light vehicles [Leq(Lv)] and heavy vehicles [Leq(Hv)] for different identified locations as well as for the entire city. Furthermore, regression noise prediction equations have been developed between Leq(o), Leq(Lv), and Leq(Hv). After comparison of the results, it can be depicted that the light motor vehicles are the main source of noise pollution in the city and gives significantly higher correlation coefficient values. This model can be applied for the calculation of road traffic noise under interrupted traffic flow conditions in urban areas of Indian cities.
本研究的主要目的是开发一种经验噪声预测模型，以评估在异质交通流条件下等效交通密度数的等效噪声水平（Leq）。选择了十个商业道路网络进行监测和建模。引入了一个新的因素，即等效轻型车辆数（EqLv）和等效重型车辆数（EqHv），用于评估每类车辆的等效交通密度，并绘制了等效交通密度与 EqLv 和 EqHv 之间的相关图，以及观测等效噪声水平[Leq（o）]，用于计算不同识别位置以及整个城市的轻型车辆[Leq（Lv）]和重型车辆[Leq（Hv）]的等效噪声水平。此外，还在 Leq（o）、Leq（Lv）和 Leq（Hv）之间建立了回归噪声预测方程。通过对结果的比较，可以描述出轻型汽车是城市噪声污染的主要来源，并给出了更高的相关系数值。该模型可用于计算印度城市市区中断交通流条件下的道路交通噪声。
