Laboratory validation study of new vapor‐phase‐based approach for groundwater monitoring

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The use of in‐field analysis of vapor‐phase samples to provide real‐time volatile organic compound (VOC) concentrations in groundwater has the potential to streamline monitoring by simplifying the sample collection and analysis process. A field validation program was completed to (1) evaluate methods for collection of vapor samples from monitoring wells and (2) evaluate the accuracy and precision of field‐portable instruments for the analysis of vapor‐phase samples. The field program evaluated three vapor‐phase sample collection methods: (1) headspace samples from two locations within the well, (2) passive vapor diffusion (PVD) samplers placed at the screened interval of the well, and (3) field vapor headspace analysis of groundwater samples. Two types of instruments were tested: a field‐portable gas chromatograph (GC) and a photoionization detector (PID). Field GC analysis of PVD samples showed no bias and good correlation to laboratory analysis of groundwater collected by low‐flow sampling (slope = 0.96, R2 = 0.85) and laboratory analysis of passive water diffusion bag samples from the well screen (slope = 1.03; R2 = 0.96). Field GC analysis of well headspace samples, either from the upper portion of the well or at the water‐vapor interface, resulted in higher variability and much poorer correlation (consistently biased low) relative to laboratory analysis of groundwater samples collected by low‐flow sample or passive diffusion bags (PDBs) (slope = 0.69 to 0.76; R2 = 0.60 to 0.64). These results indicate that field analysis of vapor‐phase samples can be used to obtain accurate measurements of VOC concentrations in groundwater. However, vapor samples collected from the well headspace were not in equilibrium with water collected from the well screen. Instead, PVD samplers placed in the screened interval represent the most promising approach for field‐based measurement of groundwater concentrations using vapor monitoring techniques and will be the focus of further field testing.

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Field Investigation of Vapor‐Phase‐Based Groundwater Monitoring

Adamson¹,

McHugh²,

Rysz³

et al. 2011

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“…This field‐portable device was equipped with two different detectors (a 10.6 eV photoionization lamp detector and an electron capture detector [ECD]); and thus was suitable for identifying and quantifying several different contaminant classes (e.g., chlorinated ethenes, chlorinated ethanes, chlorinated methanes, aromatics). This GC was employed during all phases of field testing and proved to be accurate, reliable, and sufficiently sensitive for the purposes of vapor‐phase‐based groundwater monitoring (Adamson et al , ).…”

Section: Analytical Equipmentmentioning

confidence: 99%

On‐Site Vapor‐Phase Analysis as a Novel Approach for Monitoring Groundwater Wells

Adamson¹,

McHugh²,

Rysz³

et al. 2014

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The results of comprehensive field testing of on‐site vapor‐phase‐based groundwater monitoring methods are presented to demonstrate their utility as a robust and cost‐effective approach for rapidly obtaining volatile organic compounds (VOCs) concentration data from a monitoring well. These methods—which rely on sensitive, commercially available field equipment to analyze vapor in equilibrium with groundwater—proved easy to implement and can be tailored to site‐specific needs, including multilevel sampling. During field testing, low‐flow groundwater concentrations could be reasonably estimated using submerged passive vapor diffusion samplers or field equilibration of collected groundwater (R2 = 0.85 to 0.96). These two methods are not as reliant on in‐well mixing to overcome vertical stratification within wells as simpler headspace methods. The importance of well and aquifer‐specific factors on concentration data (and therefore method selection) is highlighted, including the effect of changing in‐well patterns due to seasonal temperature gradients. Results indicated that vertical stratification was relatively limited within the set of wells included in these studies, resulting in similar performance for short depth‐discrete passive vapor diffusion samplers (constructed from 40‐mL vials) and longer samplers (2.5 to 5 feet in length) designed to cover a larger portion of the screened interval. A year‐long, multi‐event evaluation demonstrated that vapor‐phase‐based monitoring methods are no more variable than conventional groundwater monitoring methods, with both types subject to similar spatial and temporal variability that can be difficult to reduce. Vapor sampling methods represent a promising approach for estimation of groundwater concentrations by reducing the cost liabilities associated with monitoring while providing a more sustainable approach.

“…In addition to supporting the implementation of streamlined LTM programs, an improved understanding of the site‐specific sources of variability in groundwater monitoring results will improve our ability to develop and validate innovative monitoring technologies. These technologies potentially include in‐well sensors (Ho et al 2005) and vapor‐phase monitoring protocols for groundwater monitoring wells (Adamson et al 2009). In addition, it may be possible to validate such technologies for specific well designs or hydrogeologic settings while identifying other site conditions where traditional sampling methods are more appropriate.…”

Section: Introductionmentioning

confidence: 99%

Factors Influencing Variability in Groundwater Monitoring Data Sets

McHugh¹,

Beckley²,

Liu³

et al. 2011

“Random” variability in groundwater monitoring data sets reduces the ability to identify long‐term concentration trends. This, in turn, increases the time and cost required to evaluate the effectiveness of natural attenuation and other groundwater remedies. To better understand the factors influencing variability in groundwater monitoring results, we have analyzed three large groundwater monitoring data sets. For the three data sets, the long‐term trend in contaminant concentration in each well accounted for an average of 30% to 40% of the overall variation in contaminant concentration. Understanding the causes of the remaining variability would support the development of improved groundwater monitoring methods. All three data sets show large differences in the temporal monitoring records between individual wells (e.g., coefficient of variation for monitoring results from individual wells ranges from 0.08 to 4.6) indicating that well and aquifer factors are more important contributors to variability than sample collection and analysis factors. However, the depth to groundwater (R2 = 0.020) and distance between water level and screened interval (R2 = 0.049) accounted for only a portion of the differences in variability between wells and other aquifer characteristics evaluated and were not correlated with the observed variability in monitoring results. Unidentified factors were apparently much more important contributors to variability than these factors. The monitoring data sets exhibited two distinct timescales for variability: Time‐independent variability that was apparent even when wells were re‐sampled within a few days and a long‐term variability likely associated with the long‐term concentration trend. The observation of time‐independent variability suggests that frequent monitoring of contaminated monitoring wells serves primarily to characterize sources of variability unrelated to the long‐term trend of primary interest.