Using Conditional Probability to Predict Solar-Powered Pump-and-Treat Performance
Publication: Journal of Hazardous, Toxic, and Radioactive Waste
Volume 17, Issue 1
Abstract
The purpose of remediation projects is to protect human health and the environment by removing harmful substances from the environment. The carbon footprint of an environmental remediation site can be reduced by powering the project with green or sustainable energy. This paper describes a sustainable remediation project that involves the use of a single-axis passive tracking photovoltaic array to power a pump-and-treat system at a Missouri Drycleaning Environmental Response Trust Fund site. The tetrachloroethene-contaminated groundwater is pumped by way of a positive displacement piston pump and treated using granular activated carbon. Previous works studying the performance of solar-powered pumping systems were performed using known or constant water heads that are typically unknown at active remediation sites. A stochastic analysis was performed using the two inherently random variables solar radiation and pumping flow rates. Two models were developed for the estimation of the amount of water that would be pumped from a solar-powered system given (1) the amount of solar radiation observed at the site, or (2) the amount of energy consumed by the pump, both of which can be determined by using data from the free online resource PVWatts. The results showed that even given substantial effects from bioremediation activities, a long-form model was able to accurately predict data within the central range of probabilities for five of the seven months studied.
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Acknowledgments
This project was funded by the Missouri Department of Natural Resources and the Energy Resource and Development Center at Missouri University of Science and Technology.
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Published In
Journal of Hazardous, Toxic, and Radioactive Waste
Volume 17 • Issue 1 • January 2013
Pages: 31 - 37
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Nov 11, 2011
Accepted: Mar 15, 2012
Published online: Mar 19, 2012
Published in print: Jan 1, 2013
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