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Ansa E.D.O.,CSIR Water Research Institute | Awuah E.,University of Energy and Natural Resources | Andoh A.,CSIR Water Research Institute | Banu R.,CSIR Water Research Institute | And 3 more authors.
American Journal of Environmental Sciences

The use of eco-technologies for wastewater treatment such as algal and duckweed-based pond systems is becoming popular in developing countries owing to its affordability and efficiency of pathogen removal in warm climates. The pathogen removal mechanisms of these treatment systems however is still not clearly understood and existing knowledge is also scattered in journals and books of different disciplines. The purpose of this paper is to provide a concise review of knowledge acquired in recent times on faecal coliform removal mechanisms in algal and duckweed ponds in a comparative way while identifying knowledge gaps that still exist. This review pays particular attention to little known removal mechanisms such as the role of algal biomass, attachment and sedimentation of faecal coliforms and the role of predation by macroinvertebrates and protozoans. Recent experiments showed that algal ponds, in comparison with duckweed ponds, are more efficient in faecal coliform removal due to the high pH and oxygenation that occur in the former and the rate of inactivation of faecal coliforms increases with increased algal biomass till a certain optimum concentration after which it decreases. This optimal algal concentration for maximum destruction of faecal coliforms can be affected by the quality and strength of the wastewater. Algae also appeared to have a destructive effect on faecal coliforms even in darkness, a phenomenon that may be the effect of toxic substances from the algae. Results also show that the role of invertebrates, particularly macroinvertebrates may be more important in duckweed pond systems. Removal of faecal coliforms through attachment and sedimentation in both duckweed and algal ponds appear to be dependent largely on concentrations of faecal coliforms present and to some extent on suspended plant and particulate matter concentrations. Wide variations in removal efficiencies were however observed. We conclude that the wide variations in removal efficiencies can be addressed by standardizing operating conditions of treatment systems. Further work is necessary to identify the substances produced by algae which appeared to be toxic to faecal coliforms as well as establishing the relative importance of predation by protozoans and macro-invertebrates in the removal of faecal coliforms. © 2014 E.D.O. Ansa, E. Awuah, A. Andoh, H.J. Lubberding and H.J. Gijzen. This open access article is distributed under a Creative Commons Attribution (CC-BY) 3.0 license. Source

Chen Y.,CSIRO | Chen Y.,Shanghai Normal University | Yu J.,Shanghai Normal University | Yu J.,East China Normal University | Khan S.,UNESCO Regional Science Bureau for Asia and the Pacific
Environmental Modelling and Software

Criteria weights determined from pairwise comparisons are often the greatest contributor to the uncertainties in the AHP-based multi-criteria decision making (MCDM). During an MCDM process, the weights can be changed directly by adjusting the output from a pairwise comparison matrix, or indirectly by recalculating the matrix after varying its input. Corresponding weight sensitivity on multi-criteria evaluation results is generally difficult to be quantitatively assessed and spatially visualized. This study developed a unique methodology which extends the AHP-SA model proposed by Chen etal. (2010) to a more comprehensive framework to analyze weight sensitivity caused by both direct and indirect weight changes using the one-at-a-time (OAT) technique. With increased efficiency, improved flexibility and enhanced visualization capability, the spatial framework was developed as AHP-SA2 within a GIS platform. A case study with in-depth discussion is provided to demonstrate the new toolset. It assists stakeholders and researchers with better understanding of weight sensitivity for characterising, reporting and minimising uncertainty in the AHP-based spatial MCDM. © 2013 Elsevier Ltd. Source

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