Multivariate monitoring of a biological wastewater treatment process: a case study at Melbourne Water's Western Treatment Plant

Biological wastewater treatment is a complex, multivariate process, in which a number of physical and biological processes occur simultaneously. In this study, principal component analysis (PCA) and parallel factor analysis (PARAFAC) were used to profile and characterise Lagoon 115E, a multistage biological lagoon treatment system at Melbourne Water's Western Treatment Plant (WTP) in Melbourne, Australia. In this study, the objective was to increase our understanding of the multivariate processes taking place in the lagoon. The data used in the study span a 7-year period during which samples were collected as often as weekly from the ponds of Lagoon 115E and subjected to analysis. The resulting database, involving 19 chemical and physical variables, was studied using the multivariate data analysis methods PCA and PARAFAC. With these methods, alterations in the state of the wastewater due to intrinsic and extrinsic factors could be discerned. The methods were effective in illustrating and visually representing the complex purification stages and cyclic changes occurring along the lagoon system. The two methods proved complementary, with each having its own beneficial features. (C) 2003 Elsevier B.V. All rights reserved.

Additional signalling compounds are required to orchestrate plant development

Plants are necessarily complex systems that require monitoring of multiple environmental signals and, in response to those signals, coordination of differentiation and development of an extensive array of cell types at multiple locations. This coordination must rely on integration of long-distance signals that provide a means of communication among different plant parts. We propose that the relatively well-characterized classical phytohormones must act with several other long-distance signals to achieve this level of organization with dynamic yet measured responses. This is supported by observations that classical phytohormones: (i) operate in complex yet experimentally unresolved networks involving cross-talk and feedback, (ii) are generally multifunctional and nonspecific and hence must rely on other long-distance cues or pre-set conditions to achieve specificity and (iii) are likely to mask roles of other long-distance signals in several experimental contexts. We present evidence for involvement of novel long-distance signals in three developmental processes-branching, flowering and nodulation, and discuss the possible identities of novel signalling molecules.

A contour plot approach that uses data accumulated during routine monitoring to obtain insights into lagoon behaviour

Regular monitoring of wastewater characteristics is undertaken on most wastewater treatment plants. The data acquired during this process are usually filed and forgotten. However, systematic analysis of these data can provide useful insights into plant behaviour. Conventional graphical techniques are inadequate to give a good overall picture of how wastewater characteristics vary, with time and along the lagoon system. An approach based on the use of contour plots was devised that largely overcomes this problem. Superimposition of contour plots for different parameters can be used to gain a qualitative understanding of the nature and strength of relationships between the parameters. This is illustrated in an analysis of monitoring data for lagoon 115 East at the Western Treatment Plant, near Melbourne, Australia. In this illustrative analysis, relationships between ammonia removal rates and parameters such as chlorophyll a level and temperature are explored using a contour plot superimposition approach. It is concluded that this approach can help improve our understanding, not only of lagoon systems, but of other wastewater treatment systems as well.