Mohammed, A and Babatunde, AO orcid.org/0000-0003-4730-9673 (2017) Modelling heavy metals transformation in vertical flow constructed wetlands. Ecological Modelling, 354. pp. 62-71. ISSN 0304-3800
Abstract
Constructed wetlands are dynamic ecosystems for which we generally have poor predictive capabilities of the succession relationships between the interdependent components and the processes. In this study, a dynamic simulation model that can evaluate the transport and fate of heavy metals in vertical flow constructed wetland systems was developed using a dynamic software program: Structural Thinking Experiential Learning Laboratory with Animation (STELLA) v9.0.2. The key heavy metals transformation processes considered in the study were adsorption and plant uptake; whilst the forcing functions considered were wastewater volume, temperature, heavy metals concentration, contact time, flow rate and adsorbent media. The model results indicate that up to 89%, 91% and 91% of Pb, Cr and Cd respectively, can be removed through adsorption process; whereas uptake by plants was 6%, 5.1% and 5.2% based on mass balance calculations. Sensitivity analysis also showed that the most sensitive areas in the model coincide with the adsorption parameter (the heterogeneity factor (n) and the Freundlich constant (Kf)). The results obtained indicates that the model can be used to simulate outflow heavy metal concentrations, and it can also be used to estimate the amount of heavy metal removed by individual processes in the system.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 Published by Elsevier B.V. This is an author produced version of a paper published in Ecological Modelling. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Constructed wetland; Ferric sludge; Heavy metals; STELLA |
Dates: |
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Institution: | The University of Leeds |
Depositing User: | Symplectic Publications |
Date Deposited: | 02 Jun 2017 10:47 |
Last Modified: | 31 Mar 2018 00:39 |
Published Version: | https://doi.org/10.1016/j.ecolmodel.2017.03.012 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.ecolmodel.2017.03.012 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:117201 |