Measurement of active biomass in activated sludge mixed liquor

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Over the past two decades significant advances have been made in the areas of engineering (design) and technology (implementation and operation) of the single sludge activated sludge system. Activated sludge systems have been successfully designed and implemented at full-scale for the biological removal of carbon (C), nitrogen (N) and phosphorus (P). This implementation has been aided by the development of a suite of steady state design models (e.g., WRC, 1984; Wentzel et al., 1990; Maurer and Gujer, 1994) and kinetic simulation models (e.g. Dold et al., 1980, 1991; Van Haandel et al., 1981; Henze et al., 1987; Wentzel et al., 1992; Henze et al., 1995). These models constitute a common conceptualization of the processes acting in the bioreactor of the activated sludge system, based on the understanding of the interactions between the mixed liquor components and the influent wastewater. Fundamental to the steady state design and kinetic simulation models for activated sludge systems is the parameter heterotrophic active biomass (X8 u, mgAVSS/l as measured per the VSS test, or Zm-r, mgCOD/l as measured per the COD test). This mixed liquor organic suspended solids component mediates the biodegradation processes of COD removal and denitrification (and associated processes). In addition, in the models all the relevant specific process rates associated with the heterotrophic active biomass are expressed in terms of it. More recently, with the proliferation of kinetic simulation computer programmes that invariably include active biomass concentrations as parameters (e.g. Biowin, Simba, GPX, UCTOLD, UCTPHO), the active mass parameters and the use of specific rates in terms of them, have become much more widely accepted. However, XH exists only hypothetically within the structure of the design procedures and kinetic models. Although indirect evidence does provide support for this parameter (by consistence between observations and predictions over a wide range of conditions, e.g. Dold et al., 1980, 1991; Alexander et al., 1980; Van Haandel et al., 1981; Warner et al., 1986), due to the lack of suitable experimental techniques, it has not been directly measured experimentally and compared to the hypothetical model values. This deficiency casts a measure of uncertainty on the entire framework within which the models have been developed and is a major weakness in the models, namely the lack of independent quantification of the active biomass, specifically XH. Parallel to the developments in the engineering and technology of the activated sludge system, significant advances have been made in the microbiological and biochemical areas of activated sludge. In pai1icular, the development of a number of new analytical techniques to study microorganisms in situ, e.g. ATP analysis (Nelson and Lawrence, 1980), DNA analysis (Liebeskind and Dohmann, 1994), quinone profiling (Hu et al., 1998), micro autoradiography (Nielsen et al., 1998) and using florescent probes for ribosomal RNA (Wagner et al., 1994; Wat. Sci. Technol., 1998), has shown promise of providing quantitative information. While the microbiological and biochemical knowledge and developments have made a considerable contribution to the understanding of the biological nutrient removal activated sludge system, the full potential of these developments have yet to be realised for the system. It remains for the results that these techniques provide to be integrated with the design and kinetic modelling theory. The consequence of this is that the engineering and technology (modelling) paradigm has largely worked independently of the microbiological and biochemical paradigm. One area that can form a starting point to build bridges between the two paradigm sets, is measurement of heterotrophic active biomass. Additionally, this will address the main area of deficiency in the models identified above. This research project investigates measurement of heterotrophic active biomass within the engineering and technology (modelling) paradigm. If this parameter can be successfully quantified within this paradigm and agreement obtained between the measurements and the theoretical modelling values, this will provide the basis for future comparison with the quantitative data arising from the new measurement techniques within the microbiological and biochemical paradigm. This will establish a common link between the two paradigm sets