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We conducted 35 experiments for spatial measurement of marijuana aerosols in a current smoker's residential spaces. Fine particulate matter (PM2.5) concentrations were measured every second at 1, 2, and 3 m horizontal distances from the smoker who performed prescribed 5-min smoking and vaping activities. In each experiment, five SidePak monitors measured PM2.5 concentrations at five different angles facing the front of the smoker, representing the worst-case exposures. We studied the effect of distance from the smoker for two marijuana sources - smoking a marijuana cigarette, or joint, and vaping a liquid-cartridge vaping pen. Experiments were conducted in the family room indoors and in the backyard outdoors where the smoker normally consumes marijuana. Indoor marijuana vaping had higher average exposures (5-min PM2.5) at 1 m distance than indoor marijuana smoking, but the levels from indoor vaping decreased more rapidly with distance (e.g., 77% reduction for vaping versus 33% for smoking from 1 to 2 m). Smoking and vaping in the outdoor environment reduce the average exposures down to 20% indoors at 1 m). Plotting the frequency of exceedance versus distance could offer additional guidance for a recommended minimum distance from a marijuana source.

Cooking is the main source of ultrafine particles (UFP) in homes. This study investigated the effect of venting range hood flow rate on size-resolved UFP concentrations from gas stove cooking. The same cooking protocol was conducted 60 times using three venting range hoods operated at six flow rates in twin research houses. Size-resolved particle (10–420 nm) concentrations were monitored using a NanoScan scanning mobility particle sizer (SMPS) from 15 min before cooking to 3 h after the cooking had stopped. Cooking increased the background total UFP number concentrations to 1.3 × 103 particles/cm3 on average, with a mean exposure-relevant source strength of 1.8 × 1012 particles/min. Total particle peak reductions ranged from 25% at the lowest fan flow rate of 36 L/s to 98% at the highest rate of 146 L/s. During the operation of a venting range hood, particle removal by deposition was less significant compared to the increasing air exchange rate driven by exhaust ventilation. Exposure to total particles due to cooking varied from 0.9 to 5.8 × 104 particles/cm3·h, 3 h after cooking ended. Compared to the 36 L/s range hood, higher flow rates of 120 and 146 L/s reduced the first-hour post-cooking exposure by 76% and 85%, respectively. © 2018 Crown Copyright. Published with license by Taylor & Francis Group, LLC.

Cooking is one of the main sources of indoor air pollutants, and may even exceed the contribution from outdoor sources. This pilot study examines the use of different flow-rate fans during cooking and tests whether continuing to run the fan after cooking significantly improves pollutant removal rates and integrated exposures. Tests were carried out in the Canadian Centre for Housing Technology's twin research houses, in Ottawa, Ontario. We completed the same cooking protocol 60 times on a gas stove, testing 6 different flow rates on three different over-the-range exhaust fans, while continuously measuring UFP, PM2.5, NO2, and NO. The fan was operated during cooking for all tests and then either turned off or left on after cooking for the duration of the three hour test. We estimated decay rates, source emission rates, and integrated exposures to measured pollutants following the cooking test. The results showed that while leaving the fan on after cooking generally increased decay rates, it had a relatively small effect on integrated exposures compared to the effects of fan flow rate and the specific fan used during cooking. For PM2.5, the effect of running an exhaust fan for 15 min after cooking was similar in magnitude to the impact of a 100 cfm increase in the flow rate used while cooking: both were associated with a decrease in 15-min integrated exposure of roughly 3 μg m−3. This suggests that one can partially compensate for a low flow rate exhaust fan by continuing to run the fan after cooking.

Recently, a hypothesis providing a detailed equation for the Plantower CF_1 algorithm for PM2.5 has been published. The hypothesis was originally validated using eight independent Plantower sensors in four PurpleAir PA-II monitors providing PM2.5 estimates from a single site in 2020. If true, the hypothesis makes important predictions regarding PM2.5 measurements using CF_1. Therefore, we test the hypothesis using 18 Plantower sensors from four datasets from two sites in later years (2021–2023). The four general models from these datasets agreed to within 10% with the original model. A competing algorithm known as "pm2.5 alt" has been published and is freely available on the PurpleAir API site. The accuracy, precision, and limit of detection for the two algorithms are compared. The CF_1 algorithm overestimates PM2.5 by about 60–70% compared to two calibrated PurpleAir monitors using the pm2.5 alt algorithm. A requirement that the two sensors in a single monitor agree to within 20% was met by 85–99% of the data using the pm2.5 alt algorithm, but by only 22–74% of the data using the CF_1 algorithm. The limit of detection (LOD) of the CF_1 algorithm was about 10 times the LOD of the pm2.5 alt algorithm, resulting in 71% of the CF_1 data falling below the LOD, compared to 1 % for the pm2.5 alt algorithm. [ABSTRACT FROM AUTHOR]

Spatial variation of indoor and outdoor PM2.5 within three states for a five-year period is studied using regulatory and low-cost PurpleAir monitors. Most of these data were collected in an earlier study (Wallace et al., 2022 Indoor Air 32:13105) investigating the relative contribution of indoor-generated and outdoor-infiltrated particles to indoor exposures. About 260 regulatory monitors and ~10,000 outdoor and ~4000 indoor PurpleAir monitors are included. Daily mean PM2.5 concentrations, correlations, and coefficients of divergence (COD) are calculated for pairs of monitors at distances ranging from 0 (collocated) to 200 km. We use a transparent and reproducible open algorithm that avoids the use of the proprietary algorithms provided by the manufacturer of the sensors in PurpleAir PA-I and PA-II monitors. The algorithm is available on the PurpleAir API website under the name "PM2.5_alt". This algorithm is validated using several hundred pairs of regulatory and PurpleAir monitors separated by up to 0.5 km. The PM2.5 spatial variation outdoors is homogeneous with high correlations to at least 10 km, as shown by the COD index under 0.2. There is also a steady improvement in outdoor PM2.5 concentrations with increasing distance from the regulatory monitors. The spatial variation of indoor PM2.5 is not homogeneous even at distances < 100 m. There is good agreement between PurpleAir outdoor monitors located <100 m apart and collocated Federal Equivalent Methods (FEM). [ABSTRACT FROM AUTHOR]