A simple tool to help decision making in infrastructure planning and management of phytotreatment ponds for the treatment of nitrogen-rich water : technical note

In situ experimental studies were carried out aimed at the quantitative estimation of biological processes involved in nitrogen removal such as macro-algal assimilation and bacterial denitrification and their optimisation in two experimental phyto-treatment ponds colonised by the macro-algae Ulva ri...

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Veröffentlicht in:Water S. A. 2006-10, Vol.32 (4), p.605-609
Hauptverfasser: Nizzoli, Daniele, Viaroli, Pierluigi, Vezzulli, Luigi, Naldi, Mariachiara, Bartoli, Marco, Fabiano, Mauro, Fanciulli, Giorgio
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Sprache:eng
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Zusammenfassung:In situ experimental studies were carried out aimed at the quantitative estimation of biological processes involved in nitrogen removal such as macro-algal assimilation and bacterial denitrification and their optimisation in two experimental phyto-treatment ponds colonised by the macro-algae Ulva rigida in central Italy. Results from an in situ manipulative experiment estimate that Ulva carrying capacity defined as the macro-algal biomass in which the uptake of dissolved inorganic carbon (DIC) equals the production of oxygen (O2), was close to 300g·m-2 dry biomass (dw). At this carrying capacity the experimental assessment of Ulva growth rates and Ulva assimilation rates and their optimisation with use of a logistic model estimated that maximum inorganic nitrogen removal (~0.04 mol N·d-1·m-2) was attained when Ulva biomass reached 150 gdw·m-2 and growth rate was 0.1·d-1. Denitrification rates accounted for a small amount of total nitrogen removal (~150 µmol N·m-2·h-1) although an intact core incubation experiment demonstrated that denitrification increased with increasing nitrate concentrations. Based on experimental results a series of calculations have been made by use of MATLAB algorithms to facilitate manipulation of easy-to-measure variables (infrastructural, chemical and biological) and subsequent gross estimates of their effect on biological nitrogen removal efficiency, thus providing a simple tool to help decision making for infrastructure planning and management of phytotreatment ponds.
ISSN:0378-4738