January 31, 2017

Cornell Researchers Develop Comprehensive Water Quality Detector

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The water crisis in Flint, Michigan is a chilling reminder of our lack of effective freshwater management systems. Unfortunately, the list of contaminants doesn’t stop at lead. The water we drink may have hundreds of contaminants, some never even tested for by water treatment plants. However, by developing a comprehensive method to detect previously untestable pollutants in water, Prof. Damian Helbling, civil and environmental engineering, aims to change that.

According to Helbling, the motivation was to develop an analytical water screening method that would scan for a broad variety of pollutant compounds.

“What we were interested in doing was assessing water quality from the standpoint of what we call emerging chemical contaminants,” Helbling said. “So these are chemical contaminants that we suspect could be present in any particular water system but are not regulated by any local, state or federal body.”

To accomplish this, Helbling and his team developed a three step protocol to detect pollutants, including these potential chemical contaminants.

“We were able to develop a method that was comprehensive in terms of identifying analytical features that represent chemical constituents in a prepared water sample. Then we wrote a data-mining algorithm to connect those analytical features to a set of over one thousand suspect chemicals that we thought might be present,” Helbling said.

The centerpiece of this project is the use of High-Resolution Mass Spectrometry, an emerging means to detect chemical signatures based on mass.

“High-Resolution Mass Spectrometry actually can measure chemical constituents in a sample with extremely high accuracy, to the fourth or fifth decimal place of molecular mass. And when you can measure things with such high mass accuracy, you can also very accurately measure isotopic signatures,” Helbling said. “From these measurements, you can then make very good guesses as to what the elemental composition is and from there we use a variety of tricks that take us to structural elucidation.”

The list of possible pollutants is endless, so the team’s data mining algorithm systematically prioritizes known chemical signatures matched from a database. This method would allow for pollutants to be detected accurately, without the chance of false positives.

“We are not just arbitrarily selecting clear or familiar spectra, but we’re developing prioritization lists and systematically focusing on parts of these lists,” Helbling said.

Due to the robustness and versatility of this procedure, Helbling anticipates its use in environmental monitoring and medical tools.

“One application, which I would call environmental forensics, allows us to take samples of unknown composition and elucidate their chemical composition,” Helbling said. “We also use this technique to determine the structures of the intermediates of chemical reactions.”

For example, if the team was interested in a particular photolytically active — reactive to sunlight — pharmaceutical contaminant in Cayuga lake, they could use this technique to identify the structures of the breakdown products.

“This has a lot of importance when performing chemical risk assessment. You not only want to evaluate the risk of the parent chemical but any degradation products that might form, which sometimes are more toxic than the parent compound,” Helbling said.

Currently, High-Resolution Mass Spectrometry is a relatively inaccessible tool due to its costs, but Helbling hopes that as advancements continue, his method may be employed routinely for environmental monitoring.

“It expands the capabilities of traditional mass spectrometry applications in so many exciting ways. Applications in environmental chemistry are still just emerging,” he said.