IMPORTANT LEGAL NOTICE - The information on this site is subject to a disclaimer and a copyright notice.

European FlagEuropa
The European Commission

Innovation in Europe banner
Industrial Processes Title

Good neighbours in the mining business

Computer-based models and databases can predict and evaluate the environmental impact of an industrial development from the planning stage, through operation, to decommissioning and reclamation. Although the partners developed new environmental management tools for mining, these have applications in many other industries.
The project brought together two environmentally-conscious mining companies and two universities skilled in environmental modelling and computer mapping. The result is a computer-based environmental management system built around a geographical information system. Both mining companies use the new software and are pleased with its performance.

Mines and quarries are an essential part of Europe's industry, but they are often seen as bad neighbours. All over the world the mining industry is under pressure to reduce pollution from visual impact, noise, dust and fumes, road traffic and the contamination of water supplies.
Good planning and environmental management can go a long way towards eliminating these negative factors, but historically this has not been easy. The tendency has been to treat each aspect of the environmental impact as a separate phenomenon, whereas in reality many of the factors are linked in complex ways.
What the mining companies needed was a tool that would allow them to predict the potential impacts of their activities, from the early days of planning right through to the closure of the mine. This would help them choose the least harmful options at every stage. Also important was the ability to view all this data, whether predicted or measured, as an integrated whole instead of a series of isolated, and sometimes contradictory, fragments.
The environmental management system developed during this project combines the predictive capabilities of numerical models with new tools for manipulating and analysing spatial data. The system has simplified environmental impact prediction, monitoring and data analysis by coordinating them behind a single computer 'front end'.

Getting a bird's eye view

A map is often the simplest and clearest way to display predicted or measured concentrations of pollutants in the environment. Potential water pollution due to acid rock drainage from waste dumps, for instance, can be shown as a series of concentration contours spreading out through an aquifer. The map also helps engineers assess environmental impact by relating the levels of pollution to the geographic and demographic characteristics of the area.
Transparent overlays on printed maps have been used for many years, but their capabilities are rather limited. In 1990 researchers at London's Imperial College realised that a geographical information system (GIS) combined with suitable numerical models would provide the ideal tool for effective environmental management in mining.
By 1992 the Imperial College scientists were ready to start developing a full-scale system and validate it using real data. As partners they chose two mining companies: Sociedade Mineira de Neves-Corvo (Somincor), a copper and tin mine in Portugal, and Outokumpu Zinc Tara Mines, which produces zinc and lead in Ireland. The Instituto Superior Tecnico in Lisbon also joined the team to supply expertise in geostatistical modelling.

The importance of modelling

One of the main objectives of BE-5174 was to develop environmental prediction models and to integrate them with the GIS.
Imperial College developed a model of the effects of blasting in a mine. This allows the system to predict accurately the vibration levels at any point on the map, and so to design blasting regimes to remain below the prescribed vibration levels and reduce their impact on nearby people and buildings.
The Imperial College researchers also produced an air pollution model for point source emissions, while their colleagues at the Instituto Superior Tecnico did the same for area source emissions. The models are similar to the Gaussian plume dispersion models used by the US Environmental Protection Agency, but with some significant improvements. By modelling the complex behaviour of dispersion in the atmospheric boundary layer, the Imperial College researchers improved the accuracy of the predictions.
They also simplified the meteorological data requirements of the model. This is important in the minerals extraction industry as operations are often located in remote areas where full-scale meteorological monitoring may be impractical.
The Instituto Superior Tecnico concentrated on water, developing a river quality model and methods of analysing groundwater quality from monitored water quality indicators. Using geostatistics, a discipline originally developed in the mining industry for estimating ore reserves, the researchers are able to estimate pollutant levels accurately while reducing the amount of data that needs to be collected.
By identifying the critical points on the map and taking measurements here, instead of at random, the system helps make the best use of environmental technologists' time in the field. The predictive capability of the environmental management system was further increased by the development of groundwater and solute transport model at Imperial College.

Putting it on [e1]the map

Just as important as the modelling is the ability to interpret and analyse the results. The researchers at Imperial College used ARC/INFO, a widely used GIS, as a basis for the system's graphical user interface. They then integrated the various models with the GIS in a simple, flexible architecture that links the predictive power of the models with the spatial analysis and mapping capabilities of the GIS. The system runs on a standard workstation.
Environmental managers wanting to assess the effects of air pollution on the surrounding plant life, for instance, might combine a map of different vegetation types with predicted pollution concentration contours. The system can also show how environmental impacts vary with time, using either predictions from the models or real historical data from monitoring programmes.

Wider distribution within the mining world

Both Tara and Somincor are using the new system to manage their day-to-day activities. Developing a comprehensive environmental database for each mine has needed considerable effort, but both companies feel that the work has been worthwhile and that they have benefited from the project.
The developers are now keen to see the software used by the mining community worldwide. Imperial College is currently exploring various alternatives so that the prototype system can be turned into an industry-standard package with the necessary technical support.
For the future, say the developers, the system could benefit from more work on river water quality modelling, perhaps using neural networks. It would be possible, they say, to predict environmental quality indicators such as acidity and conductivity in the river from information about the mine's effluent and past data on river quality and flowrates. Imperial College is currently developing a far-field noise prediction model to extend the system's capability.
An environmentally acceptable mine is possible, believes the industry, but convincing the public of this has historically not been easy. Good environmental management will help improve both the industry's performance and its reputation.


Project Title:  
Environmental simulation and impact assessment system for the mining industry

Industrial and Materials Technologies (BRITE-EURAM/CRAFT/SMT)

Contract Reference: BE-5174

Cordis DatabaseFor more information on this project,
go to the CORDIS Database Record