Skip to main content
European Commission logo print header

The Development and Implementation of New Generation Water Quality Sensor Systems for Mines and Landfill Sites


Water resources bear fundamental importance for human survival and overall environmental balance. The nature of mineral extraction operations, surface of underground, and subsequent waste disposal and discharge activities create a potential pollution hazard for water resources around mines and tailings dam sites. Solid waste landfills are ubiquitous throughout Europe, serving as one of the principal methods of dealing with the large volume of per capita waste produced every day. Regulations have been imposed or are being recommended at the European Union and individual member state regarding the employment of water quality monitoring schemes. Such monitoring is essential for all types of landfills at all stages, commencing from the measurement of "background" levels of water quality parameters for both surface and ground waters prior to construction of the facility, during its operational life and well after its operational life and well after its final closure in order to prevent and/or mitigate pollution in the vivinity of industrial sites in Europe.
Current groundwater monitoring procedures aroundlandfills, mines and tailings ponds are extremely labour intensive and, therefore, costly. Commercially available water quality monitoring sensors need frequent maintenace and calibration by an experienced technician. The increasing demands placed upon the analytical capabilities of the landfill and mining facilities, particularly when a large number of instruments need to be deployed , may make it prohibitive to introduce and maintain an effective monitoring programme by the target industries. The mining and landfill management industries have a number of special requirements for the use of continuous monitoring equipment:

The key environmental indicators considered are pH, conductivity, temperature, redox potential, dissolved oxygen, ammonia, ammonium, nitrate, chlorides, pressure and piezometric level.
The equipment must be low cost, robust, able to operate in
chemically hostile environments and require minimum maintenance. Preferably, sensors should be self cleaning.
The measurements must be accurate and not subject to the lowest possible drift due to time, temperature or pressure changes. Calibration of the systems must be automated to allow and facilitate accurate measurements.
The sensor system must be compatible with automated continuous monitoring and data transmission.
The sensors must be installed in conditions representative of the water body or ground water under surveillance.
The data must be in a format that can be viewed rapidly in graphic form and compared with previous values.

The objective of this project is to address the above requirements by developing a robust, low cost "new generation " water sensor systems which can operate, unattended, for extended periods of time (up to three months). This objective will be achieved through the execution of the following main tasks:
Review of historical groundwater quality data at mines and landfill sites.
Incremental development of low cost and robust new generation water monitoring sensors.
Development of a new generation penetrometric sampling system which will en ble a detailed and accurate characterisation of groundwater resources/quality and will complement the use of water quality sensors at all stages of industrial operations at mines, landfill sites and in contaminated land.
Research into the spatio-temporal behaviour of groundwater
pollutants around mines and landfill sites and the development of a water quality management software for use with the sensors and the monitoring system developed.
Laboratory testing validation of the different generations of hardware and software as they are developed.

Call for proposal

Data not available


Imperial College of Science Technology and Medicine
EU contribution
No data
Prince Consort Road
SW7 2BP London
United Kingdom

See on map

Total cost
No data

Participants (3)