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High Purge Volume Sampling—A New Paradigm for Subslab Soil Gas Monitoring
Author(s) -
McAlary Todd A.,
Nicholson Paul J.,
Yik Lee K.,
Bertrand David M.,
Thrupp Gordon
Publication year - 2010
Publication title -
groundwater monitoring and remediation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.677
H-Index - 47
eISSN - 1745-6592
pISSN - 1069-3629
DOI - 10.1111/j.1745-6592.2010.01278.x
Subject(s) - soil gas , environmental science , sampling (signal processing) , soil science , spatial variability , volume (thermodynamics) , soil water , variogram , hydrology (agriculture) , kriging , petroleum engineering , geology , statistics , computer science , geotechnical engineering , mathematics , physics , filter (signal processing) , quantum mechanics , computer vision
Subslab soil gas sampling and analysis is a common line of evidence for assessing human health risks associated with subsurface vapor intrusion to indoor air for volatile organic compounds; however, conventional subslab sampling methods have generated data that show substantial spatial and temporal variability, which often makes the interpretation difficult. A new method of monitoring has been developed and tested that is based on a concept of integrating samples over a large volume of soil gas extracted from beneath the floor slab of a building to provide a spatially averaged subslab concentration. Regular field screening is also conducted to assess the trend of concentration as a function of the volume removed to provide insight into the spatial distribution of vapors at progressive distances away from the point of extraction. This approach minimizes the risk of failing to identify the areas of elevated soil vapor concentrations that may exist between discrete sample locations, and can provide information covering large buildings with fewer holes drilled through the floor. The new method also involves monitoring the extraction flow rate and transient vacuum response for mathematical analysis to help interpret the vapor concentration data and to support an optimal design for any subslab venting system that may be needed.