Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.marpolbul.2011.03.033
Title: ANN application for prediction of atmospheric nitrogen deposition to aquatic ecosystems
Authors: Palani, S. 
Tkalich, P. 
Balasubramanian, R. 
Palanichamy, J.
Keywords: Aquatic ecosystems
Atmospheric deposition
Eutrophication
Neural network
Nitrogen
Southeast Asia
Issue Date: Jun-2011
Source: Palani, S., Tkalich, P., Balasubramanian, R., Palanichamy, J. (2011-06). ANN application for prediction of atmospheric nitrogen deposition to aquatic ecosystems. Marine Pollution Bulletin 62 (6) : 1198-1206. ScholarBank@NUS Repository. https://doi.org/10.1016/j.marpolbul.2011.03.033
Abstract: The occurrences of increased atmospheric nitrogen deposition (ADN) in Southeast Asia during smoke haze episodes have undesired consequences on receiving aquatic ecosystems. A successful prediction of episodic ADN will allow a quantitative understanding of its possible impacts. In this study, an artificial neural network (ANN) model is used to estimate atmospheric deposition of total nitrogen (TN) and organic nitrogen (ON) concentrations to coastal aquatic ecosystems. The selected model input variables were nitrogen species from atmospheric deposition, Total Suspended Particulates, Pollutant Standards Index and meteorological parameters. ANN models predictions were also compared with multiple linear regression model having the same inputs and output. ANN model performance was found relatively more accurate in its predictions and adequate even for high-concentration events with acceptable minimum error. The developed ANN model can be used as a forecasting tool to complement the current TN and ON analysis within the atmospheric deposition-monitoring program in the region. © 2011 Elsevier Ltd.
Source Title: Marine Pollution Bulletin
URI: http://scholarbank.nus.edu.sg/handle/10635/58952
ISSN: 0025326X
DOI: 10.1016/j.marpolbul.2011.03.033
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