Low-flow purging and sampling methods are commonly used to monitor groundwater but are expensive because of the time required for parameter stabilization during purging and costs associated with purge water handling and disposal. Alternative no-purge methods are now available, but some are limited by analyte type and others are limited due to concerns about where in the well bore the sample comes from and whether they can accurately represent certain Department of Defense (DoD)-critical compounds such as trichloroethene (TCE). Given the high costs associated with long-term monitoring, a sampling method that is less costly but still able to yield high quality data is needed. The objectives of this project were to demonstrate that the Snap Sampler can provide technically defensible analytical data at substantial cost savings for the wide spectrum of analytes that are of concern to DoD.
The Snap Sampler is a passive groundwater sampling device that can be used to capture whole water samples at a specific point in time. The Snap Sampler system holds single or multiple bottles that are open at both ends during deployment and downhole equilibration. The equilibration period provides three things: (1) recovery from disturbance caused by placing the device in the well; (2) reestablishment of the natural flow pattern in the well; and (3) chemical equilibration of the materials in the sampler and bottles with analytes in the well. Predeployment prevents losses of analytes due to sorption by the sampler materials—a potential problem for plastic sampling devices and even pump discharge tubing. Also, by allowing time for the well to recover prior to collecting the sample, artifact particles are less likely to be entrained in the sample. Once the equilibration period is complete, the Sampler is triggered and the downhole sample bottles are sealed under in situ conditions. In the case of Snap Sampler VOA vials, samples can be prepared for laboratory submittal without exposing sample, further reducing potential for analyte losses and variability associated with well-head sample handling. A peer-reviewed scientific journal article is now available for the method as well as an ASTM Standard.
Laboratory comparisons were conducted at the Cold Regions Research and Engineering Laboratory (CRREL) in Hanover, New Hampshire. Multiple comparisons were conducted in the lab using a standpipe and measured control samples. Dissolved concentrations of several volatile organic compounds (VOCs), metals, and explosives were tested. Field demonstrations were conducted at CRREL and other field locations, including the former Pease Air Force Base (AFB) in Portsmouth, New Hampshire; the former McClellan AFB in Sacramento, California; the Louisiana Army Ammunition Plant (LAAP) in Minden, Louisiana; and the Silrism Sanitary Landfill in Lowell, Massachusetts. Field comparisons included multiple well comparisons at each site. Each monitoring well was sampled using a combination of Snap Samplers, Regenerated Cellulose (RGC) passive diffusion samplers, and U.S. Environmental Protection Agency low-flow purging and sampling protocol. Analytes measured at the Pease site included total and dissolved concentrations of arsenic (As), calcium (Ca), iron (Fe), magnesium (Mg), manganese (Mn), potassium (K), and sodium (Na). At LAAP, explosives were sampled. At Silrism, VOCs were sampled. At McClellan, samples were collected for a range of analyte types including dissolved and total inorganics (non-metal anions, metalloids, and metals), three chlorinated solvents, and MTBE. The performance criteria included the following: (1) could the method be used to collect samples for a range of contaminants; (2) could the method provide reproducible results; and (3) was there agreement between the passive sampling methods and low-flow purging and sampling for the analytes of interest.
For the laboratory study, the Snap Sampler and control samples matched for all analytes tested, including VOCs, explosives, perchlorate, metals, and other inorganics, showing no statistical difference in paired samples for all analyte types.
For the field sampling, there was excellent agreement between analyte concentrations in the Snap Sampler and low-flow sampling. These relationships were linear with the slopes nearly equal to 1.0. There were no statistically significant differences between analyte concentrations in the Snap Sampler and the low-flow sampling for the VOCs, dissolved inorganics, total non-metal anions, and most of the total metals and metalloids. The exceptions to this were for unfiltered Fe (at the Pease and McClellan sites) and unfiltered Mn (at the McClellan site) where concentrations were statistically higher in the Snap Sampler samples. However, this result may have been an artifact of turbidity associated with installation of multiple devices. There were no differences found in filtered metals samples. In some cases, there was high variability in duplicates for both the low-flow and Snap Sampler sampling, although these were often for concentrations near the reporting limit. Overall, the field implementation showed consistently good agreement between the Snap Sampler and the low flow comparator.
The Snap Sampler was found to be relatively easy to use, yielded results equivalent to low-flow sampling, and provided substantially lower sampling costs. Long-term monitoring costs were extrapolated for two demonstration sites assuming that there were 50 wells and that quarterly sampling was conducted over 10 years. The cost savings associated with using the Snap Sampler was 46% and 67% for McClellan and Pease, respectively. Much of the cost savings was a result of the reduced sampling time needed to collect samples and reduction of waste handling and disposal cost. Compared to other no-purge sampling methods, the Snap Sampler yielded a very similar long-term cost advantage, without a risk of analyte limitation or divergence from equivalence to low-flow purging and sampling techniques. Limitations of the Snap Sampler method include a requirement for 2-inch or larger monitoring wells and a sample volume constraint for certain analytes or longer analyte lists.
Key conclusions from this project include: