This study examines major wildfires in the western United States between 2005 and 2015 to determine which species exhibit the highest percent change in mass concentration on day of peak fire influence relative to preceding nonfire days. Forty‐one fires were examined using the Environmental Protection Agency (EPA) Interagency Monitoring of Protected Visual Environments (IMPROVE) data set. Organic carbon (OC) and elemental carbon (EC) constituents exhibited the highest percent change increase. The sharpest enhancements were for the volatile (OC1) and semivolatile (OC2) OC fractions, suggestive of secondary organic aerosol formation during plume transport. Of the noncarbonaceous constituents, Cl, P, K, NO3−, and Zn levels exhibited the highest percent change. Dust was significantly enhanced in wildfire plumes, based on significant enhancements in fine soil components (i.e., Si, Ca, Al, Fe, and Ti) and PMcoarse (i.e., PM10–PM2.5). A case study emphasized how transport of wildfire plumes significantly impacted downwind states, with higher levels of fine soil and PMcoarse at the downwind state (Arizona) as compared to the source of the fires (California). A global model (Navy Aerosol Analysis and Prediction System, NAAPS) did not capture the dust influence over California or Arizona during this case event because it is not designed to resolve dust dynamics in fires, which motivates improved treatment of such processes. Significant chloride depletion was observed on the peak EC day for almost a half of the fires examined. Size‐resolved measurements during two specific fires at a coastal California site revealed significant chloride reductions for particle aerodynamic diameters between 1 and 10 μm.

This work examines particulate chloride (Cl) and bromide (Br) depletion in marine aerosol particles influenced by wildfires at a coastal California site in the summers of 2013 and 2016. Chloride exhibited a dominant coarse mode due to sea salt influence, with substantially diminished concentrations during fire periods as compared to nonfire periods. Bromide exhibited a peak in the submicrometer range during fire and nonfire periods, with an additional supermicrometer peak in the latter periods. Chloride and Br depletions were enhanced during fire periods as compared to nonfire periods. The highest observed %Cl depletion occurred in the submicrometer range, with maximum values of 98.9% (0.32-0.56 μm) and 85.6% (0.56-1 μm) during fire and nonfire periods, respectively. The highest %Br depletion occurred in the supermicrometer range during fire and nonfire periods with peak depletion between 1.8-3.2 μm (78.8% and 58.6%, respectively). When accounting for the neutralization of sulfate by ammonium, organic acid particles showed the greatest influence on Cl depletion in the submicrometer range. These results have implications for aerosol hygroscopicity and radiative forcing in areas with wildfire influence owing to depletion effects on composition.

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Abstract. The formation of sulfate and secondary organic aerosol mass in the aqueous phase (aqSOA) of cloud and fog droplets can significantly contribute to ambient aerosol mass. While tracer compounds give evidence that aqueous-phase processing occurred, they do not reveal the extent to which particle properties have been modified in terms of mass, chemical composition, hygroscopicity, and oxidation state. We analyze data from several field experiments and model studies for six air mass types (urban, biogenic, marine, wild fire biomass burning, agricultural biomass burning, and background air) using aerosol size and composition measurements for particles 13–850 nm in diameter. We focus on the trends of changes in mass, hygroscopicity parameter κ, and oxygen-to-carbon (O ∕ C) ratio due to chemical cloud processing. We find that the modification of these parameters upon cloud processing is most evident in urban, marine, and biogenic air masses, i.e., air masses that are more polluted than very clean air (background air) but cleaner than heavily polluted plumes as encountered during biomass burning. Based on these trends, we suggest that the mass ratio (Rtot) of the potential aerosol sulfate and aqSOA mass to the initial aerosol mass can be used to predict whether chemical cloud processing will be detectable. Scenarios in which this ratio exceeds Rtot∼0.5 are the most likely ones in which clouds can significantly change aerosol parameters. It should be noted that the absolute value of Rtot depends on the considered size range of particles. Rtot is dominated by the addition of sulfate (Rsulf) in all scenarios due to the more efficient conversion of SO2 to sulfate compared to aqSOA formation from organic gases. As the formation processes of aqSOA are still poorly understood, the estimate of RaqSOA is likely associated with large uncertainties. Comparison to Rtot values as calculated for ambient data at different locations validates the applicability of the concept to predict a chemical cloud-processing signature in selected air masses.

This study reports a characterization of the real part of dry particle refractive index (n) at 532 nm based on airborne measurements over the United States, Canada, the Pacific Ocean, and the Gulf of Mexico from the 2012 Deep Convective Clouds and Chemistry (DC3) and 2013 Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC 4 RS) campaigns. Effective n values are reported, with the limitations and uncertainties discussed. Eight air mass types were identified based on criteria related to gas-phase tracer concentrations, location, and altitude. Average values of n for these air types ranged from 1.50 to 1.53. Values of n for the organic aerosol (OA) fraction (n OA ) were calculated using a linear mixing rule for each air mass type, with 1.52 shown to be a good approximation for all OA. Case studies detailing vertical structure revealed that n and n OA increased with altitude, simultaneous with enhancements in the mass fraction of OA. Values of n OA were positively (negatively) correlated with the O:C (H:C) ratio in the absence of biomass burning influence; in contrast, the cumulative data set revealed a slight decrease in n OA as a function of the O:C ratio. The performance of parametric (multiple linear regression) and nonparametric (Gaussian process regression) methods in predicting n based on aerosol composition data is discussed. It is shown that even small perturbations in n values significantly impact aerosol optical depth retrievals, radiative forcing, and optical sizing instruments, emphasizing the importance of further improving the understanding of this important aerosol property.