Garbage in, garbage out
Michael Scott, SWIG, argues that, with limited or even no confidence in data from process and environmental modelling sensors, what's the point?
Following the adoption of EC Directive 21, May 1994, the UK UWWTD (England
Wales) Regulations 1994 place new demands on both industry in general and,
more specifically, those involved in water and waste treatment. There
exists, then, some urgency in the drive to establish more confidence in,
comparability between, measurements. As Terry Long of the Environment
said at a recent SWIG Workshop: ³Self monitoring is very different from
went before, and now the Agency will want to assess the effectiveness of
process generating the discharge. There is a complicated set of rules to
One way to help establish confidence is to establish common practice and
procedures via accepted standards. The Environment Agency has established a
Monitoring Certification Scheme, MCERTS, to improve the quality of
environmental monitoring data. MCERTS was initially introduced for
Continuous Emission Monitoring Systems for chimney stacks, to provide
regulators and industry with improved data quality on releases from
industrial processes. WRc has a project underway, jointly funded by the
Environment Agency and GAMBICA, to expand the coverage of MCERTS to include
water monitoring instruments.
The basis of MCERTS is to provide the format for formal product
certification of monitoring instruments. Product certification is based on
laboratory and field testing, using International or European Standards
where possible. In the area of continuous water monitors (CWMs) there are
few standards which adequately define performance standards and conformance
tests; with the exception of certain flowmeters. Therefore, there is an
intention to develop the MCERTS performance standards and conformance tests
to include CWMs.
Extensive work has been carried out on instrument standards in the past and
work is ongoing at both European and intenational levels; notably including
that of PISEG, CENELEC, the Agency, SCA, ETACS and ISO. Some individual
water companies have produced instrument specifications, and others are
known to have similar work in progress.
Performance standards and conformance tests need to be designed to
demonstrate that the instrument is ³fit for purpose², and due care should
taken to ensure that the performance standards are based on the purpose of
the measuring system not necessarily on what is achievable.
Lack of confidence
Some lack of confidence in the quality of sensor data arises from the
different methods and cultures in laboratory determinations and
made on the process or in the environment. Operational standards must
incorporate a thorough understanding of the analytical standards that are
defined in regulation and the potential differences between the analytical
methods used in the laboratory and those used by the CWM. This becomes
particularly important when it is necessary to define conformance tests
based on comparisons with a reference analytical method, as opposed to the
use of a certified reference material (CRM).
The quality of data and the confidence in the data produced by on-line
monitors is also due in part to the cost of ownership of the instrument. So
whilst the cost and ease of operating, calibrating and validating
instruments is not strictly the domain of a regulatory standard, these
factors are important in obtaining good quality data over the long term and
so may need to be addressed within the performance standards.
A wide variety of tools is used to generate process and environmental data
and there is considerable business advantage in developing methods of
combining the data from different sources, places, operators and times in a
way which provides increased understanding and confidence.
At a recent SWIG Workshop, Dr Martin Lloyd, Farside Technology, emphasised
that the title of his presentation, Combining Disparate Data, was
the emphasis for his approach was one of ³combining², and not the currently
fashionable ³fusion². A great deal of work has been undertaken by Oxford
University on the SEVA validity codes, which describe the various aspects
a measurement and its robustness, but there was further work to be done
extending these definitions. Using extended versions of SEVA it has been
shown that any measurement data, regardless of source, uncertainty, time
spatial considerations, can be fitted into a single database. Visualisation
tools can then be made available to cluster data for a particular site or
investigation. Tools can be made available to make it easier to see whether
the data set has deficiencies and where extra data might improve the
To gain confidence that a process or environmental process is properly
understood, monitored and controlled, we need to have benchmarks or
standards and we need to combine data from different sources so as to
increase our knowledge.