National Physical Laboratory

Guide to Predictive Modelling for Environmental Noise Assessment


2.    Environmental Noise Modelling

2.1   Introduction

Management of the risks associated with using noise predictions requires clear communication of the relevant issues between practitioners and the end users of the information. It is therefore necessary for all parties involved to have some appreciation of what is involved when producing environmental noise models and the range of approaches that can be adopted. In particular, what it is that a noise model will represent, for which types of applications do models offer useful information, and what are the relative benefits and limitations of modelling compared to other types of objective assessment?

The following provides an overview of environmental noise modelling to address these types of questions, and thus provide a basis on which non-technical parties can engage with practitioners.

2.2   What is Environmental Noise Modelling?

Environmental noise modelling describes the process of theoretically estimating noise levels within a region of interest under a specific set of conditions.

The specific set of conditions for which the noise is being estimated will be a fixed representation or 'snapshot' of a physical environment of interest. However, in practice the physical environment will usually not be fixed, but will be characterised by constantly varying conditions. These variations in real world conditions will subsequently cause the actual sound field to vary in time and space. Thus it is important to recognise that the output of an environmental noise model will only represent an estimate for a ‘snapshot’ of the range of actual environmental noise levels that could occur in time and space.

Recognising that modelling is a means of estimating noise for a specific set of conditions, attention is now directed to defining what these conditions are. The key conditions that a noise model relates to are:

  • An approximation of the noise source, or sources, for which associated environmental noise levels are of interest
  • An approximation of the physical environment through which noise will transmit from the noise source(s) to the location or region of interest. This includes the ground terrain, the built environment, and atmospheric conditions (e.g. wind, temperature, humidity)
  • An approximation of the way in which sound will travel from the input noise source(s) via the input physical environment, to the receiver location or region of interest

Thus, producing an environmental noise model involves defining a series of noise sources to be investigated, describing acoustically significant features of the environment through which sound will propagate to the receiver, and then applying a calculation method that accounts for these descriptions to produce an estimated noise level at a location or region of interest. To demonstrate this concept, Figure 1 below provides a schematic illustration of the simplest type of environmental noise model, involving a single sound source, radiating sound via a single transmission path, to a single location in the surrounding space:

Figure 1

Figure 1:  The simplest type of model


In practice, environmental noise models will often be more complex, involving multiple sound sources, transmitting via multiple complex transmission paths, to multiple locations of interest.

In these more complex scenarios, the environmental noise model is repetitiously calculated for each sound source, via each transmission path to each and every receiver location. The total sound level at each position is then calculated by summing the contribution of each source and transmission path.

Application of these calculations to each point on a uniformly distributed grid enables a noise contour map to be developed to depict regions of equal estimated noise level and depict trends in the spatial pattern of the sound field:

Figure 2

Figure 2:  Example contour map produced from an environmental noise model

 

 

 

 

 

 

 

 

 

 

 

 

 

Last Updated: 21 Apr 2011
Created: 8 Nov 2010