May 11, 2018

New Water Treatment Plant to Implement Stanford-developed Energy Creation Technology

The technology produces energy through the wastewater cleaning process

New water treatment plant to implement technology that produces energy from treatment process

A newly-constructed water treatment plant built in Redwood Shores, Calif., will implement new technology developed at Stanford University that utilizes the treatment process to create energy. The technology utilizes anaerobic bacteria and will be supported by a $2 million grant from the California Energy Commission (CEC).

The new plant will be built alongside a much a larger standard treatment plant, supplementing its operations. Construction recently began and is expected to be completed and opened in the fall of 2018.

The anaerobic plant will process up to 20,000 gal of wastewater per day , allowing for the gathering of information and legitimization of the plant, as it has the potential to grow into a full-scale treatment facility treating millions of gallons of wastewater per day.

“Anaerobic processing can reduce energy use and decrease costs, and make wastewater treatment more sustainable,” said Craig Criddle, professor of civil and environmental engineering at Stanford University.

Switching from traditional aerobic practices to newer anaerobic technology will allow treatment plants to significantly reduce costs spent on powering blowers that provide the oxygen aerobic bacteria needs to survive. Anaerobic bacteria is oxygen-averse. Methane gas is also a natural byproduct of the anaerobic process, further incentivizing the technology, as it can be utilized as fuel or chemical feedstock.

While the long-term effects of such anaerobic technology used in the treatment process are yet to be seen, the Stanford University researchers that a fully anaerobic plant may save as much as $3,000 per day in relation to a traditional aerobic plant. This amounts to an annual saving of approximately $1,000,000, but the scientists believe this figure could potentially be doubled if efficiency is optimized.

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