28.09.2009 | Autor / Editor: J. Harper / Marcel Dröttboom
If fugitive particulate emissions are perceived to be significant, a facility may face increased regulatory requirements, more stringent environmental licence conditions and poor community relationships, which may potentially impact on the continuing operation of the facility.
There are several methods to reduce particulate emissions. These range from engineering solutions, such as enclosing the source, installing wet or dry scrubbers and conveyor belt washing, to traditional methods of dust suppression using water cannons and water trucks. However, it is becoming increasingly apparent that the dust reduction methods being used are insufficient to reduce particulate emissions to a level that is acceptable to the community or regulators.
Ore mining, handling, processing and transport activities generate dust through either wind or the physical movement of ore through mechanical processes.
The amount of particulate matter generated by wind is highly dependent upon the wind speed. Below the wind speed threshold, no particulate matter is generated, while above the threshold, particulate matter generation tends to increase with the cube of the wind speed.
The amount of particulate matter generated by wind is also dependent on the material’s surface properties. This includes whether the material is crusted, the amount of non-erodible particles and the size distribution of the material.
Mechanical processes that generate and potentially release particulate matter include comminution (crushing, screening and grinding), material movement (transfer points, stacking, reclaiming and ship loading), blasting and vehicular movement over unsealed or dust laden surfaces. The amount of particulate matter generated from these processes is less dependent on wind speed in comparison to wind erosion, but is more dependent on the moisture properties of the material being transferred, the particle size distribution of the material, drop heights and the dust management measures and emission controls in place for the sources.
A range of methods are available to measure and characterise the dust generation tendencies of various ores during handling processes.
Emission characterisation is one of the critical steps in dust management; you cannot manage what you do not know. It is essential for any facility trying to reduce dust emissions and related impact to fully understand the processes that lead to emissions. The potential emission characteristics of an ore can be determined before mining and processing by using well-established laboratory tests. Ideally, the results of the tests are used to determine the potential for both mechanical and wind-generated emissions.
For a facility already in operation, it is advisable that field measurements be used to complement the laboratory testing to fully understand the sources and causes of emissions.
Laboratory testing can be used to determine the emission characteristics of ore and help determine potential emissions before material handling commences, therefore allowing appropriate dust reduction strategies to be incorporated during the initial design phase, and reducing the need to retrofit dust reduction equipment.
Rotating Drum Test: A rotating drum test can determine the dust extinction moisture (DEM) of each ore type and its dust / moisture relationship. This helps determine the potential emissions from each ore type during material handling processes across a range of moisture contents.
Durham Cone Test: This test helps determine the moisture concentration in which flow handling issues become apparent and will define the upper limit of the moisture band (Standards Australia 2002).
Wind Tunnel Testing: To help understand the wind erosion potential of various products it is advisable to conduct wind tunnel testing. This testing will determine the minimum wind speed at which various ores will become an issue and allow various management strategies to be incorporated to reduce or eliminate this type of emission.
Particle Sizing: This test involves sieving the product and determining the percentage of material that is classified as ‘ultra fine’ (or below about 15 microns). Particles below this size have two issues:
This technique involves sampling a dust plume downwind of the source to generate dust profiles. These, along with measurements of the wind speed, distance down wind and atmospheric stability, can be used to estimate the dust emission rate for that particular source.
To obtain a comprehensive understanding of the emissions from each source, transects of the dust plume are conducted over a range of wind speeds and, if applicable, product types. An empirical equation that represents the line of best fit (as derived from the site testing) is determined and used to represent the emissions for each product from the transfer station.
If the emission rate is found to vary with the moisture content of the ore, this can be incorporated into the equation.
When all the sources at a facility have been characterised, the equations derived can be used to determine the emission rate for each source for every hour of the year. Sources from a facility may include, but are not be limited to:
To effectively use a dispersion model for emission reduction, the information obtained from both field and laboratory testing has to be integrated; this ensures the dispersion model accurately reflects the emission sources from a given facility. The most appropriate and cost-effective reduction strategies targeted at the largest emission sources can then be identified and implemented.
There are several dispersion models that can be used to predict the ground level concentrations that result from a facility and its operation. The choice of model depends on the complexity of the terrain around the facility, the availability of meteorological data and the type of sources within the facility.
Regardless of the model used, the basic methodology is the same. The model is run using the calculated emission rates for all sources within the facility and the predicted ground level concentrations are determined for applicable receptors, such as a residence or site of significance. Ideally, the model is validated against monitoring data to determine the accuracy of predicted concentrations. This validation process requires a minimum of one year of monitoring data and it is preferable that the monitoring data is from at least two monitoring locations. Ideally, the first monitor should be located at a sensitive receptor while the second should be a background monitor well away from the facility. Such a site is essential for determining the background dust concentration within the area and will help determine the dust concentration attributable to the facility.
Once the model has been validated and there is sufficient confidence that the calculated emission rates accurately reflect what is occurring at the facility, the next modelling stage can begin. This involves determining the contribution of each individual emission source to dust concentrations at the sensitive receptor.
Having identified the significant dust generation contributors at the receptors of interest, the next step is to focus on targeted control measures. This is done by determining why each of these sources is dusty when considering dust reduction strategies to ensure the most relevant reduction mechanisms are implemented.
When examining the reduction strategy for each source, it is imperative to determine the cost of implementing that strategy to ensure the facility receives the most effective reduction.
Using the validated dispersion model together with operational process information and real-time meteorological data, there is potential for a facility to monitor its emissions and determine their impact in real time. By using real-time modelling, a facility can monitor the emission rate from multiple sources to determine which process results in the highest emissions and take corrective action before it becomes an issue.
Although real-time modelling can be incorporated into the dust reduction strategy for a facility it is still a reactive method. These methods will always require the prompt attention of personnel to initiate the chosen controls, and as the alarms are only activated once certain conditions are met, the reduction strategies initiated may be “too little too late”.
It is preferable to know 24-48 hours in advance if the expected meteorological and operating conditions are conducive to a facility having an issue at a receptor.
To use this forecasting capability to its full potential, the results of the model should be analysed by another programme that references the facility’s dust management plan. This ensures that not only are the results of the model interpreted with respect to the various reduction strategies a facility has, but the appropriate personnel are notified. The notification includes what action is required to be completed by what time to prevent high emissions from occurring.
The first critical step towards reducing dust emissions is emission characterisation; you cannot manage what you do not know. This can be achieved through both laboratory testing and field measurements. Incorporating the laboratory results and field measurements in an atmospheric dispersion model helps determine which sources from a facility are impacting various sensitive receptors. The most appropriate and cost-effective reduction strategies targeted at the largest emitters can then be identified and implemented.
The atmospheric dispersion models should be used as part of a facility’s ongoing dust management plan. These can be used in either real-time mode to monitor for high emissions and adverse meteorological conditions so that corrective action can be implemented, or in a predictive mode which allows a facility to determine their potential impact 24-48 hours in advance. Predictive modelling has the potential to greatly help facilities reduce their dust emissions to an acceptable level.
Sinclair Knight Merz
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