An overview of traditional and emerging noise management approaches, and a discussion of their potential drawbacks and benefits
The management approaches adopted for environmental emissions such as noise, dust and odour (to name a few) are very often conservative or reactive in nature. These approaches are usually adopted because environmental emissions are technically complex and their level of impact is dynamically changing according to weather conditions and a mine’s operations.
This creates tension in the relationship between a mine and a community. The mine wants to maintain production, while the community is unconcerned about production and wants the mine’s emissions to be at or below the legal limits at all times. A third tension is introduced by the emission itself, which, due to its technical complexity and dynamic nature, can often create a level of uncertainty surrounding the actual impact of the mine’s emission on the community at any given time.
This last tension often leads to disputes and at times intense arguments between the mine, the community and the regulator. In order to relieve these tensions, the management approach needs, as far as possible, to remove uncertainty and provide evidence to demonstrate to the community and the regulator that the emissions are being effectively managed.
This article focuses on one emission: environmental noise. It will discuss the various noise management approaches, and how the technical complexities, dynamic conditions and uncertainty of environmental noise emissions are addressed by each approach.
The article will first look at traditional noise management approaches, and end with an emerging and exciting integrated approach that offers additional value and benefit. It is important to note that even though noise is the focus of this article, the principals and concepts that will be discussed are directly applicable to all other emissions.
In order to evaluate the different approaches and determine their performance, a scorecard needs to be established that can be used to compare and weigh each approach. In developing a scorecard, two things need to be considered: the tensions between the mine and the community, and what is required for an environmental management system (EMS) of which noise is a subset.
Environmental management systems
A good reference for an EMS can be found on the department of Environment and Energy website at www.environment.gov.au/node/20494.
In summary, an EMS is required to be a tool for managing the impacts of an organisation’s activities on the environment; it needs to provide a structured approach to planning and implementation and it needs to be integrated into a company’s daily operations and long-term planning. Figure 1 shows the continuous improvement cycle, a required concept for all environmental management systems.
Additionally, in order to address the tensions between the mine and the community, the noise management system needs to minimise shutdowns due to noise, it needs to be evidence based to demonstrate to the community that noise is being managed effectively, and it needs to be simple and fast to use without the need for intervention from a noise expert. These eight criteria can be used as a scorecard for determining the effectiveness of each noise management approach.
Noise management approaches
Noise management can be distilled down to the four approaches shown in Figure 2 and explained in the following section.
Reactive monitoring, as the name implies, is a noise management approach that responds to complaints from the community. It is only acted upon in the event of a complaint. This is by far the cheapest approach, but depending on the situation could spiral into a long-term dispute with the community and the regulator. Furthermore, the lag between the complaint and monitoring can lead to frustrations and no firm resolution in addressing the complaint. In some cases it may increase the tension between the mine and the community rather than provide relief.
Short-term compliance monitoring (ie monitoring at specified locations for a couple of months every year) as part of licence conditions also typically falls into this category. As this is driven by regulatory compliance, it does not necessarily have the same risks as those associated with a complaint reactive monitoring approach.
Real-time monitoring is a noise monitor (or network of noise monitors) that are usually wirelessly connected to provide real-time measured noise data. This approach allows the mine to react to alarms and manage their noise as they are mining. Real-time monitoring is usually adopted when a mine is located in an area that is in close proximity to a community, or when licence conditions require long-term monitoring at specific locations.
This is often seen as the answer to a mine’s noise issues. Unfortunately, real-time monitoring and data interpretation is often more complex than originally expected. The major source of this complexity is in determining the mine’s contribution to the noise field at the monitoring location. Simply put, the mine is only responsible for its noise and it is therefore important to separate out the sources of all the other noise. As noise measured at the monitor is cumulative, it can be very difficult, or at times impossible, to separate the mine’s noise from all other noise that is being measured. This results in uncertainty in the mine’s contribution and difficulty in determining if any action is required.
Another limitation of real-time monitoring is that it only provides feedback at one geographic location, while in reality the community is spread over a far wider range. This can be partially resolved by creating a network of noise monitors to provide more coverage. However, as monitors are expensive, the extent of this network is limited by the cost of implementation.
Real-time monitoring and static modelling
When a mine starts to manage noise using the real-time monitoring approach, it usually finds that threshold alarms are triggered frequently and at times spuriously. This results in personnel having to spend time assessing these alarms to determine if they are attributable to the mine or to an extraneous source. If it is determined that the received level is primarily due to the mine, then the next step is to either make operational changes or switch equipment off. This is a difficult and complex decision to make, as it affects production. Furthermore, there is often uncertainty in what a final operational configuration will look like and if this configuration will reduce levels to comply with the threshold level.
In order to assist personnel in this difficult decision-making process, a mine will employ an expert to model a number of operational scenarios under different meteorological conditions. These scenarios are then used to give guidance to operations on what equipment to switch off.
There are a number of advantages in including modelling in a noise management approach. Modelling helps you understand the noise impacts on the whole community and, unlike monitoring, it is not limited to a single location. It also helps operators to adaptively manage operations to prevent an exceedance of regulatory levels before they occur.
Due to the dynamic nature of weather and operations, there is an infinite number of scenarios that static scenario modelling will never be able to cover. The number of possible modelled scenarios are therefore limited by cost and the sheer volume of permutations.
The integrated noise management approach is an emerging and exciting technology, with systems already available on the market. This approach combines a noise monitoring network with a noise modelling capability that can deliver measured and modelled results in real time. It overcomes the limitations of static modelling, as it can model all possible permutations of the mine and weather. When combined with a monitoring network, it provides a comprehensive picture of the noise field within a community, as well as giving operations the ability to adaptively manage activities to prevent threshold levels being exceeded.
As these integrated systems collect large amounts of data, they can be used to consolidate comprehensive reports and evidence for regulatory reporting and community consultation. The integrated approach also helps remove monitoring uncertainty, as the measured levels can be compared with predicted modelled levels. This provides insight into what a mine’s contribution is to the measured noise field. Another advantage of these systems is that they are relatively cheap and require less real-time monitoring systems than other approaches.
Environmental noise, like any other emission, can be managed using a number of approaches, all of which have pros and cons depending on the mine’s situation. The effectiveness of each approach is measured by its ability to address the tensions between the mine, the community and the regulator.
The technical complexity of noise as a subject matter, and the difficulties in removing uncertainty in a mine’s compliance position, are challenges that traditional management approaches have been unable to overcome. The emerging integrated approach is an advancement in overcoming some of the limitations faced by traditional approaches, and offers an effective management approach that is cost-effective and adds a number of additional benefits.
Figure 3 graphically presents the outcomes of a scorecard-based methodology to evaluate the different noise management approaches. The figure shows each approach measured against effectiveness in fulfilling the requirements of an EMS and cost (both ongoing and implementation), with the size of the bubble representing overall value (ie operational value, quantity of meaningful evidence, simplicity and speed).
As shown, the integrated approach offers a cost-effective and value-add approach to the mine and the community. These benefits should be considered when evaluating other traditional noise management approaches.
This article is based on an AusIMM webinar delivered by Granger Bennet in March 2017. The webinar is available to purchase via www.ausimm.com.au/learning.
Feature image Andrey N Bannov/Shutterstock.com.