Making environmental management more efficient and cost-effective
In recent years, there has been a rapid adoption of proactive environmental management at mines and related industries such as ports. These have been driven by governmental requirements, new environmental standards, public awareness, changing technologies and cultural shifts in the mining industry.
An example is seen in Queensland, where new ambient air quality standards for particulate matter with a diameter less than ten µm (PM10) have been in effect since 2008. With this, the 24-hour PM10 standard dropped from 150 µg/m3 to 50 µg/m3. This has changed the mining industry profoundly regarding dust management. With a typical background level from 15 µg/m3 to 30 µg/m3, there is less capacity for the incremental dust impacts from proposed mining activity or expansion. Demonstrating compliance by desktop modelling assessment therefore becomes more difficult, time consuming and expensive. This is exacerbated by uncertainties in the assessment process, including uncertainties in the emissions, meteorology and dispersion models. As a consequence, ongoing dust monitoring has become one of the many requirements for mining project approvals.
Another driver for more proactive environmental management is the rapid development of mapping technologies and improved computer technology. When these are integrated with environmental science, potentially powerful environmental management tools are created. These tools can combine different scientific fields to extract the right intelligence from the expanding environmental data collected. The intelligence is available to mining environmental managers as informative maps and daily reports, thereby providing tailored solutions for their specific
Mining professionals are increasingly willing to embrace technologies when they can see that science and technology can be simple to use, and that it will make management more efficient and cost-effective.
New directions in thinking
During the same period there has been a profound change in the culture of mining environmental management. The old school of thinking that environment is a cost to mining companies and the ‘do nothing’ response is the more compelling option is no longer valid in the current social environment.
The social environment and community concerns will dictate the long-term public perception of a company or industry. When environment consideration is important for a business, it is best to do it well and do it cost-effectively. This is where technology helps.
Proactive environmental management tools for mining can have many uses,
- customised weather forecasting
- air quality management
- noise management
- blast management
- environmental data management
- complaints management
- environmental compliance reports.
Dust management at mines is an issue as old as mining itself. Modern dust management is all about knowing the types of emissions, adopting effective yet economical options to mitigate them and implementing management practices to bring levels of dust at nearby sensitive receptors to compliance.
Dust management can often be difficult as many complex factors are in play. Proactive dust management that incorporates technologies can be much simpler. Technological tools link these complex factors ‘behind the scenes’ logically and scientifically, generating final intelligence in formats for the relevant responsible mine personnel. The overall structure is transparent, but contains multiple models that involve sophisticated physics, chemistry and mathematics.
The technologies may consist of the following components: an ambient monitoring network with a data management system, a weather forecast system, an emission estimation system, a real-time or forecast system of dispersion modelling and a decision support system.
The relationship between and interactions of these components are shown in the flowchart in Figure 1.
An ambient monitoring network is often one of the conditions for mining approvals. The design of the network is generally aimed to provide a good measurement of true impacts at the nearby receptor locations. If conducted well, the measurement will become the reference points of the system, with reliable data to validate the other components in the system.
Weather forecasts tailored for a specific location used to be a challenging scientific endeavour and hence were not widely used for mining management in the past. In recent years, the development and wide adoption of the Weather Research and Forecast (WRF) model for weather forecasts, coupled with improved computing capabilities, has made this task more attainable.
With WRF forecast meteorology, various dispersion modelling methods (typically CALPUFF, AERMOD or particle models) can be used to predict dust impacts from mining operations, generally for up to three days in advance. The modelling systems will be able to predict dust emission rates based on forecast wind and other weather conditions such as direction and rainfall, and it will predict ground-level dust concentrations at nearby residential or other sensitive receptors. In addition, the meteorological forecasts can be used to make timely decisions regarding workplace safety, for example, potential high wind, temperature, thunderstorm or rainfall events.
WRF, CALPUFF and AERMOD are all sophisticated models that are developed and used by scientists that specialise in these areas. To make the results more useful for mining environmental managers, they need to be presented in simple yet informative formats.
Advances in geographic information system (GIS) mapping in the past two decades have transformed the appearance of information technology. There are no longer standalone charts and tables, but rather geographically relevant graphs shown with multiple map layers. IT professionals are working with scientists to make proactive dust management tools informative yet easy to use.
Figure 2 shows an example of a real-time dust monitoring display, indicating areas of concern for reactive management.
Acting on forecast and real-time information prevents potential environmental problems and unlocks operational constraints before they occur. For example, the provision of forecast warnings during periods of high dust risk allows operational plans and controls to be made in advance. This includes alternative operating scenarios, optimising resources for emission control or implementing alternative productive activities such as training
Blasting is a concern for noise (due to overpressure) and air quality. Explosives that contain nitrogen, normally in the form of ammonium nitrate, can produce oxides of nitrogen (NOx) when ignited under non-ideal conditions.
NOx fumes are brown clouds containing nitrogen dioxide (NO2) and nitric oxide (NO). Among these, NO2 is the most toxic to human health. There are many ways to minimise the release of NOx fumes, from the design of blasting holes to suit ground conditions and local geology to the chemical manufacturing and storage. Meteorology is another important factor to consider to minimise blasting risk. The actual meteorological conditions at the time of firing will have a significant impact on the fume plume transport and dispersion. Figure 3 shows predicted dust plumes for blasting fired at two different hours of a day. If one plume is passing through a sensitive location (diamond symbol in Figure 3) and the other is not, a blasting manager can make an informed decision on when to conduct blasting operations.
Blast overpressure may produce a shockwave and noise, resulting in a potentially dangerous situation for onsite workers and negative community reaction offsite. Figure 4 shows an example of predicted blast overpressure contours.
A proactive blasting management tool that is embedded into the standard operating procedures of a mine would therefore significantly reduce the risk of blasting fumes and overpressure on onsite workers and local residences.
A proactive blasting management tool may consist of the following components:
- a weather forecast system, the same as for the dust management system
- an emission estimation system, based on Attalla et al (2008) and Department of Sustainability, Environment, Water, Population and Communities (2012)
- a dispersion modelling system for NOx and a noise modelling system
- a decision support mapping system.
Complaints management is an integral part of an environmental manager’s role, especially where communities are located in close proximity to mines. Technology can assist in complaints management by collating complaints data, identifying the source of an issue and determining when rapid investigation and reporting is needed. A backward trajectory model can provide solid evidence to streamline source identification and enhance evidence.
A backward trajectory model (or backtrack) traces a parcel of air backward in time from a specific location. The path of the parcel is determined from 3D observational and prognostic meteorological data and can be used to prove or disprove liability arising from community dust complaints. Figure 5 shows an example of a dust complaint. In this particular example, the backward trajectory indicates that the air approached the complainant’s location from the east and consequently the mine to the south-west could not have been the source of the dust complaint.
Ambient dust monitoring
An ambient dust monitoring system is an essential component of mine dust management. More specifically, automation is the key for mine site proactive dust management. An example of automation is when high air pollution levels are registered at a monitoring station or stations (see Figure 2), an SMS or email alert can be sent automatically. These alerts can then be used to trigger appropriate actions from site managers to mitigate impacts.
It is important to note that without technology, such as a well-designed software solution to regularly detect instrument failures and unusual data behaviour, ambient monitoring programs at remote mine sites are often troubled by high percentages of missing or low-quality data. Without this technology, monitoring data needed to be manually analysed and presented in monthly or quarterly reports, only to be archived with limited management usage. Consequently, if non-compliances were found, the reactive responses would generally take a long time to formulate.
The proactive use of monitoring data will therefore ensure that more intensive mitigation measures are applied at the right time for the right activities. This means ‘effective’ and ‘cost-efficient’. This used to be unthinkable, but they have now been adopted by numerous mines and ports and many other industries.
Recent advances in weather forecasts
The WRF model is a numerical model developed by the National Center for Atmospheric Research (NCAR) and the National Oceanic and Atmospheric Administration (NOAA) in the United States. The model utilises global reanalysis data (ie past weather observational data) as initial input and global forecast model results as boundary conditions. It takes into account local terrain and land-use effects. Using WRF in this way, meteorologists are able to forecast local weather for a specific location, such as a mine or a port, anywhere in Australia and around the world. This data is a critical component of a proactive dust management system in that it not only drives blast and complaints management, but can also be used to predict adverse weather conditions for a particular mine site.
The WRF weather forecast is a community model, with multiple applications for proactive dust management. This is shown more clearly in Figure 6.
However, meteorological forecasting is an area of scientific endeavour that still needs to be done properly by qualified meteorologists, with careful consideration of model parameters and local terrain and land-use conditions. Quarterly or annual validation of model predictions against monitoring data, either onsite or from a nearby Bureau of Meteorology (BOM) station, is recommended to ensure the quality of
A local meteorological monitoring station should be an integral part of the weather forecast system. If there is no representative BOM weather station nearby, an onsite weather station should be set up, measuring the basic surface weather parameters such as wind speed, wind direction, rainfall, temperature, humidity and solar radiation.
Once a WRF weather forecast has been set up and validated, the system should provide reliable weather forecasts for mine dust, noise and other management issues affected by weather.
Current status of dust emissions estimation, measurement and controls
Dust emission is the key component of mine site dust management. Due to the fugitive nature of mine dust and fume emissions, it is difficult to conduct in-field measurements to quantify the emissions. Therefore, site-specific mining emissions are often unavailable.
NPI and AP-42 emission factors are commonly used to estimate dust emissions at mines. AP-42 is a large repository of air pollutant emission factors compiled by the United States Environmental Protection Agency (USEPA) and is readily accessible online. The National Pollutant Inventory (NPI) Emission Estimation Technique Manual for Mining (Department of Sustainability, Environment, Water, Population and Communities, 2012) provides the calculation methods and emission factors to support this reporting process. This NPI manual draws heavily from the
A recent study for the Australian Coal Industry’s Research Program (ACARP) provided a set of coal dust emission factors based on measurements recently conducted within Australia (Pacific Environment, 2015a). This study focussed on the four main particulate matter-generating activities at coal mines: hauling, bulldozing, truck loading and unloading, and wind erosion.
For critical sources of emissions, site-specific emission measurements may provide valuable insights on the overall mine emissions and inform on the efficiency of emission control measures. Recent studies commissioned by ACARP provided substantial literature reviews of measurement methods and sampling protocols available for fugitive emissions (Pacific Environment, 2015b and 2015c).
For emission control best practices, the New South Wales Office of Environment and Heritage commissioned a review entitled NSW Coal Benchmarking Study: International Best Practice Measures to Prevent and/or Minimise Emissions of Particulate Matter from Coal Mining (Donnelly et al, 2011).
Improved emissions result in improved inputs to predictive dust models, thereby resulting in improved dust predictions. This in turn gives mine management greater confidence in utilising these predictions for proactive management.
With the assistance of powerful environmental management tools currently available in the marketplace, proactive environmental management at mine sites has never been easier. These tools combine various fields of environmental science with predicted and real-time environmental data to extract the right environmental intelligence for a mine. Recent advances in GIS mapping have transformed the appearance of these tools into geographically relevant graphs shown with multiple map layers.
IT professionals are working with scientists to make environmental management tools intuitive and informative. With online services and cloud computing, the requirement for sophisticated IT infrastructure onsite has become redundant. These tools enable the management of air, noise, water and soil environment from the same web service platform.
While environmental management might not generate direct profit for mines, implementing a proactive environmental management system can improve productivity and community relations and hence generate more profit for mines.
We would like to thank the clients of Pacific Environment Limited for making this study possible. We would also like to thank the many individuals at Pacific Environments for their support, particularly Mitchell Farquhar, Vianna Tran, Robin Ormerod, Matt Scholl and Damon Roddis.
Readers can visit the Pacific Environment Ltd website at www.pacific-environment.com.
Attalla, M I, Day, S J, Lange, T, Lilley, W, and Morgan, S, 2008. NOx emissions from blasting operations in open-cut coal mining, Atmospheric Environment, 42(34):7874–7883.
Department of Sustainability, Environment, Water, Population and Communities, 2012. National Pollutant Inventory – Emission estimation technique manual for mining, Version 3.1, Canberra, Australia.
Donnelly P S-J, Balch A, Wiebe A, Shaw N, Schloss A, Castillo E, Henville K, 2011. NSW Coal Mining Benchmarking Study : International Best Practice Measures to Prevent and/or Minimise Emissions of Particulate Matter from Coal Mining, prepared for NSW Office of Environment and Heritage.
Pacific Environment, 2015a. Development of Australia-specific PM10 emission factors for coal mines, draft report, prepared for Australian Coal Industry’s Research Program.
Pacific Environment, 2015b. Development of Australia-specific PM10 emission factors for coal mines – literature review, draft report, prepared for Australian Coal Industry’s Research Program.
Pacific Environment, 2015c. Development of Australia-specific PM10 emission factors for coal mines – protocols for sampling and data analysis, draft report, prepared for Australian Coal Industry’s Research Program.
Queensland Department of Employment, Economic Development and Innovation, 2011. Management of oxides of nitrogen in open cut blasting, Queensland Guidance Note QGN 20 v 3.