(56)
By experimentally monitoring the growth curves of biofilms produced by a given
microbial culture under different operating conditions, values of the parameters and b
can be correlated with variables such as substrate concentration, liquid velocity,
temperature, pH, etc. This will enable the prediction of the steady-state biofilm mass for
any set of operating conditions within the range of applicability of those parameters.
CONCLUDING REMARKS
Microbial film reactors are still calculated by means of practical design criteria that are
not based upon sound phenomenological equations such as the diffusion-reaction models.
Those procedures have been used for many years in designing wastewater biofilm
reactors but, although many processes are operating in quite acceptable conditions, some
design errors and, most probably, over-design are the natural consequence of the lack of
more reliable and precise calculation methods (Harremöes and Henze, 1995). Over-
designed reactors imply excessive capital costs, and can also result in operational
problems such as the instability of the bio-reactor due to the formation of thick biofilms
that tend to detach or slough off, causing periodic poor performances. Efficient control of
the microbial layer thickness has been discussed by several authors in the last decade
(Capdeville et al., 1992; Lazarova and Manem, 1994, 1997; Tijhuis et al., 1994) as a way
of achieving an enhanced reactor stability.
The major problems in biofilm modelling are not the unavailability of more or less
sophisticated mathematical tools. They result from the lack of correlations able to
produce values of the diffusion coefficients, the biological kinetic parameters and the
biofilm thickness as a function of the operating conditions and reactor characteristics;
from the lack of capacity to relate the composition and structure of the microbial film,
particularly the density and spatial distribution of active cells, to the conditions under
which the biofilm was formed; and from the lack of accurate information on the biomass
yield in the biofilm. Obviously, all this implies a deeper knowledge of the microbial
metabolism inside the biological matrix, including a better understanding of the
physiological state of the micro-organisms and their kinetics in the specific micro-
environment that surrounds them in a biofilm. The concurrent efforts of both engineering
science (to develop semi-empirical models that relate intrinsic parameters to external
operating and design variables) and biological science (to shed light on the behaviour of
micro-organisms in attached biomass systems) are clearly needed.
NOMENCLATURE
Af surface area of biofilm (m^2 )
As cross sectional area of the filter (m^2 )
Av specific area of support per volume of reactor (m^2 .m−^3 )
Biofilm reactors 319