The water utility HOFOR
A/S is currently implementing central drinking water softening in the Greater
Copenhagen area. In areas with hard drinking water, softening can provide a
number of positive socioeconomic and environmental effects experienced by the
end users (households or industries) due to reduced problems with lime
scaling, a longer service life of household appliances and installations, and
reduced of soap and detergents.
Softening processes often
focus on the reduction of water hardness. However, water hardness is not the
only and maybe not the most accurate indicator of the actual lime scaling in
kettles, toilets and onto tiles, and so maybe it does not reflect how water consumers
actually experience the effects of softening at home.
An alternative to
hardness is the calcium carbonate precipitation potential (CCPP) modelled in
PHREEQC to predict the lime scaling potential from a water sample. Similarly,
the measured calcium carbonate precipitation (MCCP) in a water sample can be
analyzed in the laboratory by boiling a water sample. We want to test if this
simple analysis gives a more precise indication of what users are
experiencing in terms of lime scale deposits at home.
To investigate how
the implementation of central drinking water softening in Copenhagen affects
the consumers, HOFOR A/S is interested in developing MCCP analysis in their laboratory.
With this analysis it would possible to measure and compare water samples,
from i.e. different places in Copenhagen, different technologies or different
waterworks, for instance the MCCP in water from the softening plant in
Brøndby could be compared with water from plants in the rest of the Greater
Hence, this project
aims at implementing MCCP analysis at HOFOR laboratory in close collaboration
with HOFOR lab technicians and at comparing results from MCCP analyses and
CCPP calculations using water from different waterworks and softened by
different methods. This has the potential of providing better tools for
optimizing the implemented softening technologies and predicting the water