Methane research shapes up at wastewater plant

A wastewater treatment plant in the US has used a dynamic imaging particle analysis system to monitor the condition and presence of methanogens in its anaerobic digestion process to find a potential correlation with methane production.

ESG Operations (ESG) in Augusta, Georgia, is a contract company that handles municipal utility operations. Pretty much anything a city needs to do from a wastewater and water treatment utility standpoint, ESG is contracted to operate and maintain. Methane production is becoming more of a focus for a variety of utility applications; therefore, understanding the conditions and presence of this biology has become increasingly relevant.

The anaerobic digestion process occurs when organic materials in an enclosed vessel, kept at a constant temperature, are broken down by microorganisms in the absence of oxygen. This process produces a gas consisting of methane and carbon dioxide.

At ESG, anaerobic methanogen microorganisms break down sewage sludge and wastewater solids to produce methane that can be used to produce electricity and heat. The effectiveness of this anaerobic digestion process is determined by the methanogen population.

Methane formers are very delicate organisms and they’re susceptible to dying off if you change their environment too much, so they need to be in a tightly controlled environment.

The initial study shapes up

Percy Nolan is a project manager at ESG. He acquired the use of a FlowCAM dynamic imaging particle analysis system as part of a partnership/collaboration program with Fluid Imaging Technologies. One of the things that Nolan and his team theorised when using the instrument was that there was a correlation with methane production and the presence of methanogens in their anaerobic digestion process. They knew that a specific species of bacteria, Archaea, produced methane. They also knew about what size they were and they knew their shape. They felt that if they could easily see the particles and identify the shapes using the FlowCAM, a correlation with microorganisms may emerge. Then they might be on to something.

“Having an easy way to monitor our methanogen populations throughout our process would provide us with a cost-effective way to quickly see the effect of changes or modifications,” said Nolan. “Ultimately, it has the potential to help us create a more streamlined and predictable process control strategy.”

Bacilli-shaped microorganisms (above) and grit (below) samples as imaged on the FlowCAM used at the Augusta, Georgia, treatment plant.

Nolan and his team analysed samples to determine particle shape. They found some that were the rod-shaped bacillus they believed to be Archaea particles. With its VisualSpreadsheet software, the FlowCAM can record over 30 different measurements per particle and can capture particle images at up to 22 frames per second allowing for high sampling efficiency and fast analysis times. It sorts and filters particle data and immediately displays all similar-type particles. The data they collected with the FlowCAM trended very closely to some of the performance parameters that they normally test for in their analytic digestion strains. “It was pretty exciting to see the characteristics and the fact that the particles trended so similarly,” said Nolan.

Increases in volatile solids reductions correlated to increases in image densities and decreases in CO₂ levels. CH₄ was not sampled as part of this study, so it was postulated that the decrease in CO₂ would be indicative of an increase in CH₄ levels. The correlations were surprisingly acute as it pertained to CO₂ levels. The trend graphs above demonstrate these findings.

Nolan and his team found there was definitely some correlation between the bacilli-shaped microorganism images they were seeing with the FlowCAM and what was going on in their digesters. However, more in-depth testing would need to happen over a period of time in order to verify that what they had found was, in fact, an Archaea organism that produces methane. “I feel like we were able to hypothesise in a very short, abbreviated kind of study that we were correlating something to our performance criteria that normally trends in that process,” said Nolan.

The potential

The main focus at ESG is to reduce the solids amount as much as they can through digestion. But Nolan recognises the benefit of an application of a cogeneration system where these microorganisms could be producing enough methane to power a generator for other processors in the plant.

“It would require running your digestion train in series, not in parallel in order for it to be useful — which is what we happen to do here,” said Nolan.

One of the benefits of running things the way ESG does is that there are different feeds from different areas in the plant and the tanks all have different feed characteristics. It makes it much easier to figure out where an issue is coming from and to isolate it quickly compared to combing all the feeds into one digester.

“I combine the feeds after they’ve digested for a while,” said Nolan. “This allows me to troubleshoot any problems on the initial run through the tanks well before they process to the secondary equipment tanks.”

If ESG had a FlowCAM in place, they could improve process performance. If the bacilli-shaped microorganisms turned out to be a methanogen population, they could predict with some reliability what they’re going to be able to produce for gases and subsequently estimate how much natural gas consumption was required to supplement other equipment processes. When designing cogeneration systems, the big unknown is how much gas can be produced and how well can it be captured.

For example, if it could be determined that Archaea was found, the FlowCAM would provide data on population counts.

“Through more in-depth research we would know if we have, say, 20 million of these microorganisms per millilitre, then that equates to some quantity of natural gas or methane,” said Nolan.

The speed at which ESG could get information on potential methanogen populations would be another benefit of using the FlowCAM. If the microorganisms could be genetically identified correctly and established in real time, it has the potential to save costs in digester process control at the plant.

Fluid Imaging Technologies

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