Defining Sampling Zones in Large Industrial Buildings to Select Efficient Vapor Intrusion Investigation Strategies
Designing an efficient sampling strategy for large industrial buildings can be challenging, with most regulatory guidance documents providing only limited recommendations. Targeting the areas of highest vapor intrusion (VI) potential and using supplemental indicator and tracer (I&T) data (e.g., indoor radon, differential pressure [DP]) can decrease investigation costs by reducing the number and frequency of collecting samples for laboratory analysis. Building characteristics including air exchange, indoor air mixing, indoor/outdoor temperature differences, long-term DP, and the presence of preferential pathways contribute to VI potential. Readily observable building features, such as floor area, ceiling height, or type of air handling system, can be used by investigators to identify individual sampling zones, prioritize zones that have an enhanced VI potential, and select appropriate supplemental data collection. A year-long temporal variability study was conducted in four sampling zones within a large industrial warehouse-type building. As part of the study, air exchange rates were quantitatively measured in each sampling zone followed by the collection of continuous subslab and indoor VOC, indoor/outdoor radon, subslab-to-indoor and outdoor-to-indoor DP, indoor/outdoor air temperatures, wind speed/direction, barometric pressure, and precipitation data. The study found that sampling zones can largely be defined as sets of rooms or compartments served by the same air handling system. Special considerations should be given to sub-areas that are enclosed and where vapor entry points are present, such that complete air mixing may not be occurring. The study also found that the rate of air exchange in a specific sampling zone can significantly impact the effectiveness of I&T data to predict VI. Based on this study, an approach to efficient sampling of large commercial and industrial buildings is proposed to take advantage of both field observations and I&T data.