Secondhand exposure from vaping marijuana: Concentrations, emissions, and exposures determined using both research-grade and low-cost monitors
Abstract
A popular method of inhaling marijuana is by heating marijuana liquid (vaping). We study exhaled aerosol within experimental rooms in two inhabited homes and determine peak concentrations, decay and removal rates, and source emissions. These parameters allow a simple exposure model to be developed. The experimental approach was to measure particle concentrations from one or multiple puffs of marijuana liquid within the experimental rooms. Commercial cartridges containing marijuana liquid of varying CBD:THC ratios (2:1, 7:1, 8:1, and 18:1) were compared. PM2.5 concentrations were measured continuously by optical monitors (SidePak and PurpleAir monitors) and by mass measurements (Piezobalances). The mass measurements in a subsample were verified using gravimetric (pump-filter) methods. Air exchange rates were measured using tracer gases. Calibration factors (CFs) were developed for the SidePak and Piezobalance using gravimetric analysis of their response to the aerosol produced by vaping. These CFs were 0.97 (SE 0.04) for the Piezobalances and 0.44 (SE 0.04) for the SidePaks. Comparisons with these instruments suggested a median CF for PurpleAir monitors of 3. This CF is based upon an alternative methodology for calculating PM2.5 based on the particle numbers in three size categories from 0.3 to 2.5 μm. Two preheating periods of about 3 and 12 s were adopted before a 3-s inhalation. The longer heating period produced an increase in the source strength from 3.0 (SE 0.3) to 8.8 (SE 0.3) mg/puff. PM2.5 removal rates were 0.38 (SE 0.04) h-1 for the SidePaks and 0.30 (SE 0.03) h-1 for the PurpleAir monitors. An 8-day experiment with a single puff each day from a marijuana liquid cartridge showed elevated concentrations in the small experimental room for the next 9 h. Mean concentrations during these hours were 63 μg/m3, compared to 4.5 μg/m3 at other times. A simple exposure model was developed and applied to several scenarios of low and high expected exposures.
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