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Award ID contains: 1950327

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  1. Abstract The Arctic warms nearly four times faster than the global average, and aerosols play an increasingly important role in Arctic climate change. In the Arctic, sea salt is a major aerosol component in terms of mass concentration during winter and spring. However, the mechanisms of sea salt aerosol production remain unclear. Sea salt aerosols are typically thought to be relatively large in size but low in number concentration, implying that their influence on cloud condensation nuclei population and cloud properties is generally minor. Here we present observational evidence of abundant sea salt aerosol production from blowing snow in the central Arctic. Blowing snow was observed more than 20% of the time from November to April. The sublimation of blowing snow generates high concentrations of fine-mode sea salt aerosol (diameter below 300 nm), enhancing cloud condensation nuclei concentrations up to tenfold above background levels. Using a global chemical transport model, we estimate that from November to April north of 70° N, sea salt aerosol produced from blowing snow accounts for about 27.6% of the total particle number, and the sea salt aerosol increases the longwave emissivity of clouds, leading to a calculated surface warming of +2.30 W m−2under cloudy sky conditions. 
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  2. Abstract Wildfires are a major source of gas‐phase ammonia (NH3) to the atmosphere. Quantifying the evolution and fate of this NH3is important to understanding the formation of secondary aerosol in smoke and its accompanying effects on radiative balance and nitrogen deposition. Here, we use data from the Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE‐CAN) to add new empirical constraints on the e‐folding loss timescale of NH3and its relationship with particulate ammonium (pNH4) within wildfire smoke plumes in the western U.S. during summer 2018. We show that the e‐folding loss timescale of NH3with respect to particle‐phase partitioning ranges from ∼24 to ∼4000 min (median of 55 min). Within these same plumes, oxidation of nitrogen oxides is observed concurrent with increases in the fraction ofpNH4in each plume sampled, suggesting that formation of ammonium nitrate (NH4NO3) is likely. We find wide variability in how close ourin situmeasurements of NH4NO3are to those expected in a dry thermodynamic equilibrium, and find that NH4NO3is most likely to form in fresh, dense smoke plumes injected at higher altitudes and colder temperatures. In chemically older smoke we observe correlations between both the fraction ofpNH4and the fraction of particulate nitrate (pNO3) in the aerosol with temperature, providing additional evidence of the presence of NH4NO3and the influence of injection height on gas‐particle partitioning of NH3
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  3. Abstract The Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE‐CAN) deployed the NSF/NCAR C‐130 aircraft in summer 2018 across the western U.S. to sample wildfire smoke during its first days of atmospheric evolution. We present a summary of a subset of reactive oxidized nitrogen species (NOy) in plumes sampled in a pseudo‐Lagrangian fashion. Emissions of nitrogen oxides (NOx = NO + NO2) and nitrous acid (HONO) are rapidly converted to more oxidized forms. Within 4 h, ∼86% of the ΣNOyis in the form of peroxy acyl nitrates (PANs) (∼37%), particulate nitrate (pNO3) (∼27%), and gas‐phase organic nitrates (Org N(g)) (∼23%). The averagee‐folding time and distance for NOxare ∼90 min and ∼40 km, respectively. Nearly no enhancements in nitric acid (HNO3) were observed in plumes sampled in a pseudo‐Lagrangian fashion, implying HNO3‐limited ammonium nitrate (NH4NO3) formation, with one notable exception that we highlight as a case study. We also summarize the observed partitioning of NOyin all the smoke samples intercepted during WE‐CAN. In smoke samples intercepted above 3 km above sea level (ASL), the contributions of PANs andpNO3to ΣNOyincrease with altitude. WE‐CAN also sampled smoke from multiple fires mixed with anthropogenic emissions over the California Central Valley. We distinguish samples where anthropogenic NOxemissions appear to lead to an increase in NOxabundances by a factor of four and contribute to additional PAN formation. 
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  4. Abstract. Accurate representation of aerosol optical properties is essential for the modeling and remote sensing of atmospheric aerosols. Although aerosol optical properties are strongly dependent upon the aerosol size distribution, the use of detailed aerosol microphysics schemes in global atmospheric models is inhibited by associated computational demands. Computationally efficient parameterizations for aerosol size are needed. Inthis study, airborne measurements over the United States (DISCOVER-AQ) andSouth Korea (KORUS-AQ) are interpreted with a global chemical transport model (GEOS-Chem) to investigate the variation in aerosol size when organicmatter (OM) and sulfate–nitrate–ammonium (SNA) are the dominant aerosol components. The airborne measurements exhibit a strong correlation (r=0.83) between dry aerosol size and the sum of OM and SNA mass concentration (MSNAOM). A global microphysical simulation(GEOS-Chem-TOMAS) indicates that MSNAOM and theratio between the two components (OM/SNA) are the major indicators for SNA and OM dry aerosol size. A parameterization of the dry effective radius (Reff) for SNA and OM aerosol is designed to represent the airborne measurements (R2=0.74; slope = 1.00) and the GEOS-Chem-TOMAS simulation (R2=0.72; slope = 0.81). When applied in the GEOS-Chem high-performance model, this parameterization improves the agreement between the simulated aerosol optical depth (AOD) and the ground-measured AOD from the Aerosol Robotic Network (AERONET; R2 from 0.68 to 0.73 and slope from 0.75 to 0.96). Thus, this parameterization offers a computationally efficient method to represent aerosol size dynamically. 
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  5. Abstract. The impact of biomass burning (BB) on the atmospheric burden of volatile organic compounds (VOCs) is highly uncertain. Here we apply the GEOS-Chemchemical transport model (CTM) to constrain BB emissions in the western USA at ∼ 25 km resolution. Across three BB emission inventorieswidely used in CTMs, the inventory–inventory comparison suggests that the totals of 14 modeled BB VOC emissions in the western USA agree with eachother within 30 %–40 %. However, emissions for individual VOCs can differ by a factor of 1–5, driven by the regionally averaged emissionratios (ERs, reflecting both assigned ERs for specific biome and vegetation classifications) across the three inventories. We further evaluate GEOS-Chemsimulations with aircraft observations made during WE-CAN (Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption and Nitrogen) andFIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) field campaigns. Despite being driven by different global BBinventories or applying various injection height assumptions, the model–observation comparison suggests that GEOS-Chem simulations underpredictobserved vertical profiles by a factor of 3–7. The model shows small to no bias for most species in low-/no-smoke conditions. We thus attribute thenegative model biases mostly to underestimated BB emissions in these inventories. Tripling BB emissions in the model reproduces observed verticalprofiles for primary compounds, i.e., CO, propane, benzene, and toluene. However, it shows no to less significant improvements for oxygenatedVOCs, particularly for formaldehyde, formic acid, acetic acid, and lumped ≥ C3 aldehydes, suggesting the model is missing secondarysources of these compounds in BB-impacted environments. The underestimation of primary BB emissions in inventories is likely attributable tounderpredicted amounts of effective dry matter burned, rather than errors in fire detection, injection height, or ERs, as constrained by aircraftand ground measurements. We cannot rule out potential sub-grid uncertainties (i.e., not being able to fully resolve fire plumes) in the nestedGEOS-Chem which could explain the negative model bias partially, though back-of-the-envelope calculation and evaluation using longer-term groundmeasurements help support the argument of the dry matter burned underestimation. The total ERs of the 14 BB VOCs implemented in GEOS-Chem onlyaccount for half of the total 161 measured VOCs (∼ 75 versus 150 ppb ppm−1). This reveals a significant amount of missing reactiveorganic carbon in widely used BB emission inventories. Considering both uncertainties in effective dry matter burned (× 3) and unmodeledVOCs (× 2), we infer that BB contributed to 10 % in 2019 and 45 % in 2018 (240 and 2040 Gg C) of the total VOC primaryemission flux in the western USA during these two fire seasons, compared to only 1 %–10 % in the standard GEOS-Chem. 
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  6. Wildfires are an important atmospheric source of primary organic aerosol (POA) and precursors for secondary organic aerosol (SOA) at regional and global scales. However, there are large uncertainties surrounding the emissions and physicochemical processes that control the transformation, evolution, and properties of POA and SOA in large wildfire plumes. We develop a plume version of a kinetic model to simulate the dilution, oxidation chemistry, thermodynamic properties, and microphysics of organic aerosol (OA) in wildfire smoke. The model is applied to study the in-plume OA in four large wildfire smoke plumes intercepted during an aircraft-based field campaign in summer 2018 in the western United States. Based on estimates of dilution and oxidant concentrations before the aircraft first intercepted the plumes, we simulate the OA evolution from very close to the fire to several hours downwind. Our model results and sensitivity simulations suggest that dilution-driven evaporation of POA and simultaneous photochemical production of SOA are likely to explain the observed evolution in OA mass with physical age. The model, however, substantially underestimates the change in the oxygen-to-carbon ratio of the OA compared to measurements. In addition, we show that the rapid chemical transformation within the first hour after emission is driven by higher-than-ambient OH concentrations (3×10 6 -10 7 molecules cm -3 ) and the slower evolution over the next several hours is a result of lower-than-ambient OH concentrations (<10 6 molecules cm -3 ) and depleted SOA precursors. Model predictions indicate that the OA measured several hours downwind of the fire is still dominated by POA but with an SOA fraction that varies between 30% and 56% of the total OA. Semivolatile, heterocyclic, and oxygenated aromatic compounds, in that order, were found to contribute substantially (>90%) to SOA formation. Future work needs to focus on better understanding the dynamic evolution closer to the fire and resolving the rapid change in the oxidation state of OA with physical age. 
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  7. Abstract. The evolution of organic aerosol (OA) and aerosol sizedistributions within smoke plumes is uncertain due to the variability inrates of coagulation and OA condensation/evaporation between different smokeplumes and at different locations within a single plume. We use aircraftdata from the FIREX-AQ campaign to evaluate differences in evolving aerosolsize distributions, OA, and oxygen to carbon ratios (O:C) between and withinsmoke plumes during the first several hours of aging as a function of smokeconcentration. The observations show that the median particle diameterincreases faster in smoke of a higher initial OA concentration (>1000 µg m−3), with diameter growth of over 100 nm in 8 h – despite generally having a net decrease in OA enhancementratios – than smoke of a lower initial OA concentration (<100 µg m−3), which had net increases in OA. Observations of OA and O:Csuggest that evaporation and/or secondary OA formation was greater in lessconcentrated smoke prior to the first measurement (5–57 min afteremission). We simulate the size changes due to coagulation and dilution andadjust for OA condensation/evaporation based on the observed changes in OA.We found that coagulation explains the majority of the diameter growth, withOA evaporation/condensation having a relatively minor impact. We found thatmixing between the core and edges of the plume generally occurred ontimescales of hours, slow enough to maintain differences in aging betweencore and edge but too fast to ignore the role of mixing for most of our cases. 
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  8. Abstract. Biomass burning emits vapors and aerosols into the atmosphere thatcan rapidly evolve as smoke plumes travel downwind and dilute, affectingclimate- and health-relevant properties of the smoke. To date, theory hasbeen unable to explain observed variability in smoke evolution. Here, we useobservational data from the Biomass BurningObservation Project (BBOP) field campaign and show that initial smokeorganic aerosol mass concentrations can help predict changes in smokeaerosol aging markers, number concentration, and number mean diameterbetween 40–262 nm. Because initial field measurements of plumes aregenerally >10 min downwind, smaller plumes will have alreadyundergone substantial dilution relative to larger plumes and have lowerconcentrations of smoke species at these observations closest to the fire.The extent to which dilution has occurred prior to the first observation isnot a directly measurable quantity. We show that initial observed plumeconcentrations can serve as a rough indicator of the extent of dilutionprior to the first measurement, which impacts photochemistry, aerosolevaporation, and coagulation. Cores of plumes have higher concentrationsthan edges. By segregating the observed plumes into cores and edges, we findevidence that particle aging, evaporation, and coagulation occurred beforethe first measurement. We further find that on the plume edges, the organicaerosol is more oxygenated, while a marker for primary biomass burningaerosol emissions has decreased in relative abundance compared to the plumecores. Finally, we attempt to decouple the roles of the initialconcentrations and physical age since emission by performing multivariatelinear regression of various aerosol properties (composition, size) on thesetwo factors. 
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  9. null (Ed.)