Robot chemists push aside decades-old water quality analysis tool

A U.S. Geological Survey (USGS) lab was invaded by robots this January. In this case, a friendly, robotic technology will save USGS time and money by performing analyses for dissolved nutrients. Thousands of water samples annually come through the door at USGS from widely diverse geographical locations and all types of streams, lakes, reservoirs, and groundwaters.

U.S. Geological Survey

This automated discrete analyzer began operating in January at the U.S. Geological Survey’s National Water Quality Lab. The robot is expected to dramatically speed up water sample process times and save the government money.

The robotic technology, automated discrete analyzer (DA) instruments, is pushing aside the continuous flow analyzer (CFA) technology that USGS’s National Water Quality Laboratory (NWQL) has used for decades.

DA instruments perform the same routine determinations that CFA instruments do, but with substantially reduced sample volumes and much less operator intervention and maintenance, according to Charles Patton, an analytical chemist at NWQL and the driving force in getting the DA system integrated.

“It’s really just miniaturized, roboticized test-tube chemistry where it’s very easy to do reruns and dilutions that are difficult to automate in a CFA system,” Patton explains. Instead of 360 tests per hour, the USGS lab will now be able to process 600 tests per hour. “It’s a very powerful technology that’ll really change the way we work,” he adds.

In use in the clinical world since the 1980s, DA technology has been slow to catch on in environmental laboratories, and NWQL is one of the first to make the conversion. The implications are enormous.

For starters, the USGS researchers will be able to analyze all requests for standard- and low-concentration-range dissolved-nutrient data—such as nitrate, nitrite, ammonia, and orthophosphate—on a single, low-maintenance DA instrument.

NWQL processes most of the samples collected by USGS nationwide.

Consequently, “This is a great test bed for validating new technologies and methods,” Patton notes, adding that an upcoming paper with several thousand side-by-side data points will show that DA results are statistically comparable with those of the CFA. —KRIS CHRISTEN