Seven commercial cooking oils were investigated to determine the PM_2.5 mass and ultrafine particle (UFP) emission rates and emission fluxes (rates per area). The results of this study showed that at 197°C soybean, safflower, canola, and peanut oils produced lower PM_2.5 emission fluxes (6.1 × 10⁵, 3.0 × 10⁵, 5.4 × 10⁵, and 3.9 × 10⁵ μg/min/m², respectively) than corn, coconut, and olive oils (2.7 × 10⁶, 2.9 × 10⁶, and 5.7 × 10⁶ μg/min/m², respectively). Similarly, the total particle number flux at 197°C was lower for soybean, safflower, and canola oils (3.5 × 10¹³, 8.6 × 10¹³, and 1.0 × 10¹⁴ #/min/m², respectively) than the corn, coconut, olive, and peanut oils (2.4 × 10¹⁴, 1.4 × 10¹⁴, 1.7 × 10¹⁴, and 3.8 × 10¹⁴ #/min/m², respectively). In general, oils with a higher smoke temperature resulted in lower particle concentrations over the measured temperature range (131–197°C). The percentage of UFP (particle diameter D_p 10–100 nm) to total particles (D_p 10–500 nm) ranged from 76 to 99% for this temperature range. Particles below 10 nm in diameter were not measured. The particle number size distribution showed a polydisperse behavior with major mode sizes ranging from 25 nm (for peanut oil) to 82 nm (for soybean oil) at an oil temperature of 197°C. Practical Implications The study presents particle number and mass concentrations, size distributions, emission rates, and emission fluxes from heating common cooking oils. The emission rates and emission fluxes can be used as inputs to models for indirect exposure analysis studies. The study may also be used to provide guidance on choosing oils that result in lower emission rates when heated.

Resuspension experiments were performed in a single-family residence. Resuspension by human activity was found to elevate the mass concentration of indoor particulate matter with an aerodynamic dia...

There is concern regarding the heterogeneity of exposure to airborne particulate matter (PM) across urban areas leading to negatively biased health effects models. New, low-cost sensors now permit continuous and simultaneous measurements to be made in multiple locations. Measurements of ambient PM were made from October to April 2015–2016 and 2016–2017 to assess the spatial and temporal variability in PM and the relative importance of traffic and wood smoke to outdoor PM concentrations in Rochester, NY, USA. In general, there was moderate spatial inhomogeneity, as indicated by multiple pairwise measures including coefficient of divergence and signed rank tests of the value distributions. Pearson correlation coefficients were often moderate (~50% of units showed correlations >0.5 during the first season), indicating that there was some coherent variation across the area, likely driven by a combination of meteorological conditions (wind speed, direction, and mixed layer heights) and the concentration of PM_2.5 being transported into the region. Although the accuracy of these PM sensors is limited, they are sufficiently precise relative to one another and to research grade instruments that they can be useful is assessing the spatial and temporal variations across an area and provide concentration estimates based on higher-quality central site monitoring data.