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Marine emissions of dimethyl sulfide (DMS) and the subsequent formation of its oxidation products methanesulfonic acid (MSA) and sulfuric acid (H2SO4) are well-known natural precursors of atmospheric aerosols, contributing to particle mass and cloud formation over ocean and coastal regions. Despite a long-recognized and well-studied role in the marine troposphere, DMS oxidation chemistry remains a work in progress within many current air quality and climate models, with recent advances exploring heterogeneous chemistry and uncovering previously unknown intermediate species. With the identification of additional DMS oxidation pathways and intermediate species that influence the eventual fate of DMS, it is important to understand the impact of these pathways on the overall sulfate aerosol budget and aerosol size distribution. In this work, we update and evaluate the DMS oxidation mechanism of the chemical transport model GEOS-Chem by implementing expanded DMS oxidation pathways in the model. These updates include gas- and aqueous-phase reactions, the formation of the intermediates dimethyl sulfoxide (DMSO) and methanesulfinic acid (MSIA), and cloud loss and aerosol uptake of the recently quantified intermediate hydroperoxymethyl thioformate (HPMTF). We find that this updated mechanism collectively decreases the global mean surface-layer gas-phase sulfur dioxide (SO2) mixing ratio by 40 % and enhances the sulfate aerosol (SO42-) mixing ratio by 17 %. We further perform sensitivity analyses exploring the contribution of cloud loss and aerosol uptake of HPMTF to the overall sulfur budget. Comparing modeled concentrations to available observations, we find improved biases relative to previous studies. To quantify the impacts of these chemistry updates on global particle size distributions and the mass concentration, we use the TwO-Moment Aerosol Sectional (TOMAS) aerosol microphysics module coupled to GEOS-Chem and find that changes in particle formation and growth affect the size distribution of aerosol. With this new DMS-oxidation scheme, the global annual mean surface-layer number concentration of particles with diameters smaller than 80 nm decreases by 16.8 %, with cloud loss processes related to HPMTF being mostly responsible for this reduction. However, the global annual mean number of particles larger than 80 nm (corresponding to particles capable of acting as cloud condensation nuclei, CCN) increases by 3.8 %, suggesting that the new scheme promotes seasonal particle growth to these sizes.

The capability of chemical transport models to represent fine particulate matter (PM2.5) over the course of a day is of vital importance for air quality simulation and assessment. In this work, we used the nested GEOS-Chem model at 0.25∘×0.3125∘ resolution to simulate the diel (24 h) variation in PM2.5 mass concentrations over the contiguous United States (US) in 2016. We evaluate the simulations with in situ measurements from a national monitoring network. Our base case simulation broadly reproduces the observed morning peak, afternoon dip, and evening peak of PM2.5, matching the timings of these features within 1–3 h. However, the simulated PM2.5 diel amplitude in our base case was 106 % biased high, relative to observations. We find that temporal resolution of emissions, subgrid vertical gradient between surface model-level center and observations, and biases in boundary layer mixing and aerosol nitrate are the major causes for this inconsistency. We applied an hourly anthropogenic emission inventory, converted the PM2.5 mass concentrations from the model-level center to the height of surface measurements by correcting for aerodynamic resistance, adjusted the boundary layer heights in the driving meteorological fields using aircraft observations, and constrained nitrate concentrations using in situ measurements. The bias in the PM2.5 diel amplitude was reduced to −12 % in the improved simulation. Gridded hourly emissions rather than diel scaling factors applied to monthly emissions reduced biases in simulated PM2.5 overnight. Resolving the subgrid vertical gradient in the surface model level aided the capturing of the timings of the PM2.5 morning peak and afternoon minimum. Based on the improved model, we find that the mean observed diel variation in PM2.5 for the contiguous US is driven by (1) building up of PM2.5 by 10 % in early morning (04:00–08:00 local time, LT), due to increasing anthropogenic emissions into a shallow mixed layer; (2) decreasing PM2.5 by 22 % from mid-morning (08:00 LT) through afternoon (15:00 LT), associated with mixed-layer growth; (3) increasing PM2.5 by 30 % from mid-afternoon (15:00 LT) though evening (22:00 LT) as emissions persist into a collapsing mixed layer; and (4) decreasing PM2.5 by 10 % overnight (22:00–04:00 LT) as emissions diminish.

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. In this study, airborne measurements over the United States (DISCOVER-AQ) and South Korea (KORUS-AQ) are interpreted with a global chemical transport model (GEOS-Chem) to investigate the variation in aerosol size when organic matter (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 the ratio 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.

The impact of biomass burning (BB) on the atmospheric burden of volatile organic compounds (VOCs) is highly uncertain. Here we apply the GEOS-Chem chemical transport model (CTM) to constrain BB emissions in the western USA at ∼ 25 km resolution. Across three BB emission inventories widely used in CTMs, the inventory–inventory comparison suggests that the totals of 14 modeled BB VOC emissions in the western USA agree with each other within 30 %–40 %. However, emissions for individual VOCs can differ by a factor of 1–5, driven by the regionally averaged emission ratios (ERs, reflecting both assigned ERs for specific biome and vegetation classifications) across the three inventories. We further evaluate GEOS-Chem simulations with aircraft observations made during WE-CAN (Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption and Nitrogen) and FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) field campaigns. Despite being driven by different global BB inventories or applying various injection height assumptions, the model–observation comparison suggests that GEOS-Chem simulations underpredict observed 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 the negative model biases mostly to underestimated BB emissions in these inventories. Tripling BB emissions in the model reproduces observed vertical profiles for primary compounds, i.e., CO, propane, benzene, and toluene. However, it shows no to less significant improvements for oxygenated VOCs, particularly for formaldehyde, formic acid, acetic acid, and lumped ≥ C3 aldehydes, suggesting the model is missing secondary sources of these compounds in BB-impacted environments. The underestimation of primary BB emissions in inventories is likely attributable to underpredicted amounts of effective dry matter burned, rather than errors in fire detection, injection height, or ERs, as constrained by aircraft and ground measurements. We cannot rule out potential sub-grid uncertainties (i.e., not being able to fully resolve fire plumes) in the nested GEOS-Chem which could explain the negative model bias partially, though back-of-the-envelope calculation and evaluation using longer-term ground measurements help support the argument of the dry matter burned underestimation. The total ERs of the 14 BB VOCs implemented in GEOS-Chem only account for half of the total 161 measured VOCs (∼ 75 versus 150 ppb ppm−1). This reveals a significant amount of missing reactive organic carbon in widely used BB emission inventories. Considering both uncertainties in effective dry matter burned (× 3) and unmodeled VOCs (× 2), we infer that BB contributed to 10 % in 2019 and 45 % in 2018 (240 and 2040 Gg C) of the total VOC primary emission flux in the western USA during these two fire seasons, compared to only 1 %–10 % in the standard GEOS-Chem.

Spatiotemporal control encompasses a variety of techniques for producing laser pulses with dynamic intensity peaks that move independently of the group velocity. This controlled motion of the intensity peak offers a new approach to optimizing laser-based applications and enhancing signatures of fundamental phenomena. Here, we demonstrate spatiotemporal control with a plasma optic. A chirped laser pulse focused by a plasma lens exhibits a moving focal point, or “flying focus,” that can travel at an arbitrary, predetermined velocity. Unlike currently used conventional or adaptive optics, a plasma lens can be located close to the interaction region and can operate at an orders of magnitude higher, near-relativistic intensity.

The evolution of organic aerosol (OA) and aerosol size distributions within smoke plumes is uncertain due to the variability in rates of coagulation and OA condensation/evaporation between different smoke plumes and at different locations within a single plume. We use aircraft data from the FIREX-AQ campaign to evaluate differences in evolving aerosol size distributions, OA, and oxygen to carbon ratios (O:C) between and within smoke plumes during the first several hours of aging as a function of smoke concentration. The observations show that the median particle diameter increases 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 enhancement ratios – than smoke of a lower initial OA concentration ( µg m−3), which had net increases in OA. Observations of OA and O:C suggest that evaporation and/or secondary OA formation was greater in less concentrated smoke prior to the first measurement (5–57 min after emission). We simulate the size changes due to coagulation and dilution and adjust for OA condensation/evaporation based on the observed changes in OA. We found that coagulation explains the majority of the diameter growth, with OA evaporation/condensation having a relatively minor impact. We found that mixing between the core and edges of the plume generally occurred on timescales of hours, slow enough to maintain differences in aging between core and edge but too fast to ignore the role of mixing for most of our cases.

Dimethylsulfide (DMS) emitted from seawater is a key precursor to new particle formation and acts as a regulator in Earth's warming climate system. However, DMS's effects are not well understood in various ocean regions. In this study, we estimated DMS emissions based on a machine learning method and used the GEOS-Chem global 3D chemical transport model coupled with the TwO Moment Aerosol Sectional (TOMAS) microphysics scheme to simulate the atmospheric chemistry and radiative effects of DMS. The contributions of DMS to atmospheric SO42- aerosol and cloud condensation nuclei (CCN) concentrations along with the radiative effects over the Asian region were evaluated for the first time. First, we constructed novel monthly resolved DMS emissions (0.5∘×0.5∘) for the year 2017 using a machine learning model; 4351 seawater DMS measurements (including the recent measurements made over the Chinese seas) and 12 relevant environment parameters were selected for model training. We found that the model could predict the observed DMS concentrations with a correlation coefficient of 0.75 and fill the values in regions lacking observations. Across the Asian seas, the highest seasonal mean DMS concentration occurred in March–April–May (MAM), and we estimate the annual DMS emission flux of 1.25 Tg (S), which is equivalent to 15.4 % of anthropogenic sulfur emissions over the entire simulation domain (which covered most of Asia) in 2017. The model estimates of DMS and methane sulfonic acid (MSA), using updated DMS emissions, were evaluated by comparing them with cruise survey experiments and long-term online measurement site data. The improvement in model performance can be observed compared with simulation results derived from the global-database DMS emissions. The relative contributions of DMS to SO42- and CCN were higher in remote oceanic areas, contributing 88 % and 42 % of all sources, respectively. Correspondingly, the sulfate direct radiative forcing (DRF) and indirect radiative forcing (IRF) contributed by DMS ranged from −200 to −20 mW m−2 and from −900 to −100 mW m−2, respectively, with levels varying by season. The strong negative IRF is mainly over remote ocean regions (−900 to −600 mW m−2). Generally, the magnitude of IRF derived by DMS was twice as large as its DRF. This work provides insights into the source strength of DMS and the impact of DMS on climate and addresses knowledge gaps related to factors controlling aerosols in the marine boundary layer and their climate impacts.

Atmospheric new particle formation (NPF) is a crucial process driving aerosol number concentrations in the atmosphere; it can significantly impact the evolution of atmospheric aerosol and cloud processes. This study analyses at least 1 year of asynchronous particle number size distributions from six different locations in India. We also analyze the frequency of NPF and its contribution to cloud condensation nuclei (CCN) concentrations. We found that the NPF frequency has a considerable seasonal variability. At the measurement sites analyzed in this study, NPF frequently occurs in March–May (pre-monsoon, about 21 % of the days) and is the least common in October–November (post-monsoon, about 7 % of the days). Considering the NPF events in all locations, the particle formation rate (JSDS) varied by more than 2 orders of magnitude (0.001–0.6 cm−3 s−1) and the growth rate between the smallest detectable size and 25 nm (GRSDS-25 nm) by about 3 orders of magnitude (0.2–17.2 nm h−1). We found that JSDS was higher by nearly 1 order of magnitude during NPF events in urban areas than mountain sites. GRSDS did not show a systematic difference. Our results showed that NPF events could significantly modulate the shape of particle number size distributions and CCN concentrations in India. The contribution of a given NPF event to CCN concentrations was the highest in urban locations (4.3 × 103 cm−3 per event and 1.2 × 103 cm−3 per event for 50 and 100 nm, respectively) as compared to mountain background sites (2.7 × 103 cm−3 per event and 1.0 × 103 cm−3 per event, respectively). We emphasize that the physical and chemical pathways responsible for NPF and factors that control its contribution to CCN production require in situ field observations using recent advances in aerosol and its precursor gaseous measurement techniques.

Atmospheric particulate matter smaller than 2.5 µm in diameter (PM2.5) has a negative impact on public health, the environment, and Earth's climate. Consequently, a need exists for accurate, distributed measurements of surface-level PM2.5 concentrations at a global scale. Existing PM2.5 measurement infrastructure provides broad PM2.5 sampling coverage but does not adequately characterize community-level air pollution at high temporal resolution. This motivates the development of low-cost sensors which can be more practically deployed in spatial and temporal configurations currently lacking proper characterization. Wendt et al. (2019) described the development and validation of a first-generation device for low-cost measurement of AOD and PM2.5: the Aerosol Mass and Optical Depth (AMODv1) sampler. Ford et al. (2019) describe a citizen-science field deployment of the AMODv1 device. In this paper, we present an updated version of the AMOD, known as AMODv2, featuring design improvements and extended validation to address the limitations of the AMODv1 work. The AMODv2 measures AOD and PM2.5 at 20 min time intervals. The sampler includes a motorized Sun tracking system alongside a set of four optically filtered photodiodes for semicontinuous, multiwavelength (current version at 440, 500, 675, and 870 nm) AOD sampling. Also included are a Plantower PMS5003 sensor for time-resolved optical PM2.5 measurements and a pump/cyclone system for time-integrated gravimetric filter measurements of particle mass and composition. AMODv2 samples are configured using a smartphone application, and sample data are made available via data streaming to a companion website (https://csu-ceams.com/, last access: 16 July 2021). We present the results of a 9 d AOD validation campaign where AMODv2 units were co-located with an AERONET (Aerosol Robotics Network) instrument as the reference method at AOD levels ranging from 0.02 ± 0.01 to 1.59 ± 0.01. We observed close agreement between AMODv2s and the reference instrument with mean absolute errors of 0.04, 0.06, 0.03, and 0.03 AOD units at 440, 500, 675, and 870 nm, respectively. We derived empirical relationships relating the reference AOD level to AMODv2 instrument error and found that the mean absolute error in the AMODv2 deviated by less than 0.01 AOD units between clear days and elevated-AOD days and across all wavelengths. We identified bias from individual units, particularly due to calibration drift, as the primary source of error between AMODv2s and reference units. In a test of 15-month calibration stability performed on 16 AMOD units, we observed median changes to calibration constant values of −7.14 %, −9.64 %, −0.75 %, and −2.80 % at 440, 500, 675, and 870 nm, respectively. We propose annual recalibration to mitigate potential errors from calibration drift. We conducted a trial deployment to assess the reliability and mechanical robustness of AMODv2 units. We found that 75 % of attempted samples were successfully completed in rooftop laboratory testing. We identify several failure modes in the laboratory testing and describe design changes that we have since implemented to reduce failures. We demonstrate that the AMODv2 is an accurate, stable, and low-cost platform for air pollution measurement. We describe how the AMODv2 can be implemented in spatial citizen-science networks where reference-grade sensors are economically impractical and low-cost sensors lack accuracy and stability.

Biomass burning emits vapors and aerosols into the atmosphere that can rapidly evolve as smoke plumes travel downwind and dilute, affecting climate- and health-relevant properties of the smoke. To date, theory has been unable to explain observed variability in smoke evolution. Here, we use observational data from the Biomass Burning Observation Project (BBOP) field campaign and show that initial smoke organic aerosol mass concentrations can help predict changes in smoke aerosol aging markers, number concentration, and number mean diameter between 40–262 nm. Because initial field measurements of plumes are generally >10 min downwind, smaller plumes will have already undergone substantial dilution relative to larger plumes and have lower concentrations of smoke species at these observations closest to the fire. The extent to which dilution has occurred prior to the first observation is not a directly measurable quantity. We show that initial observed plume concentrations can serve as a rough indicator of the extent of dilution prior to the first measurement, which impacts photochemistry, aerosol evaporation, and coagulation. Cores of plumes have higher concentrations than edges. By segregating the observed plumes into cores and edges, we find evidence that particle aging, evaporation, and coagulation occurred before the first measurement. We further find that on the plume edges, the organic aerosol is more oxygenated, while a marker for primary biomass burning aerosol emissions has decreased in relative abundance compared to the plume cores. Finally, we attempt to decouple the roles of the initial concentrations and physical age since emission by performing multivariate linear regression of various aerosol properties (composition, size) on these two factors.

Aerosols over Earth's remote and spatially extensive ocean surfaces have important influences on planetary climate. However, these aerosols and their effects remain poorly understood, in part due to the remoteness and limited observations over these regions. In this study, we seek to understand factors that shape marine aerosol size distributions and composition in the northwest Atlantic Ocean region. We use the GEOS-Chem model with the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithm model to interpret measurements collected from ship and aircraft during the four seasonal campaigns of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) conducted between 2015 and 2018. Observations from the NAAMES campaigns show enhancements in the campaign-median number of aerosols with diameters larger than 3 nm in the lower troposphere (below 6 km), most pronounced during the phytoplankton bloom maxima (May/June) below 2 km in the free troposphere. Our simulations, combined with NAAMES ship and aircraft measurements, suggest several key factors that contribute to aerosol number and size in the northwest Atlantic lower troposphere, with significant regional-mean (40–60∘ N and 20–50∘ W) cloud-albedo aerosol indirect effect (AIE) and direct radiative effect (DRE) processes during the phytoplankton bloom. These key factors and their associated simulated radiative effects in the region include the following: (1) particle formation near and above the marine boundary layer (MBL) top (AIE: −3.37 W m−2, DRE: −0.62 W m−2); (2) particle growth due to marine secondary organic aerosol (MSOA) as the nascent particles subside into the MBL, enabling them to become cloud-condensation-nuclei-sized particles (AIE: −2.27 W m−2, DRE: −0.10 W m−2); (3) particle formation and growth due to the products of dimethyl sulfide, above and within the MBL (−1.29 W m−2, DRE: −0.06 W m−2); (4) ship emissions (AIE: −0.62 W m−2, DRE: −0.05 W m−2); and (5) primary sea spray emissions (AIE: +0.04 W m−2, DRE: −0.79 W m−2). Our results suggest that a synergy of particle formation in the lower troposphere (particularly near and above the MBL top) and growth by MSOA contributes strongly to cloud-condensation-nuclei-sized particles with significant regional radiative effects in the northwest Atlantic. To gain confidence in radiative effect magnitudes, future work is needed to understand (1) the sources and temperature dependence of condensable marine vapors forming MSOA, (2) primary sea spray emissions, and (3) the species that can form new particles in the lower troposphere and grow these particles as they descend into the marine boundary layer.

Global observations and model studies indicate that new particle formation (NPF) in the upper troposphere (UT) and subsequent particles supply 40 %–60 % of cloud condensation nuclei (CCN) in the lower troposphere, thus affecting the Earth's radiative budget. There are several plausible nucleation mechanisms and precursor species in this atmospheric region, which, in the absence of observational constraints, lead to uncertainties in modeled aerosols. In particular, the type of nucleation mechanism and concentrations of nucleation precursors, in part, determine the spatial distribution of new particles and resulting spatial distribution of CCN from this source. Although substantial advances in understanding NPF have been made in recent years, NPF processes in the UT in pristine marine regions are still poorly understood and are inadequately represented in global models. Here, we evaluate commonly used and state-of-the-art NPF schemes in a Lagrangian box model to assess which schemes and precursor concentrations best reproduce detailed in situ observations. Using measurements of aerosol size distributions (0.003 < Dp < 4.8 µm) in the remote marine troposphere between ∼0.18 and 13 km altitude obtained during the NASA Atmospheric Tomography (ATom) mission, we show that high concentrations of newly formed particles in the tropical UT over both the Atlantic and Pacific oceans are associated with outflow regions of deep convective clouds. We focus analysis on observations over the remote Pacific Ocean, which is a region less perturbed by continental emissions than the Atlantic. Comparing aerosol size distribution measurements over the remote Pacific with box model simulations for 32 cases shows that none of the NPF schemes most commonly used in global models, including binary nucleation of sulfuric acid and water (neutral and ion-assisted) and ternary involving sulfuric acid, water, and ammonia, are consistent with observations, regardless of precursor concentrations. Through sensitivity studies, we find that the nucleation scheme among those tested that is able to explain most consistently (21 of 32 cases) the observed size distributions is that of Riccobono et al. (2014), which involves both organic species and sulfuric acid. The method of Dunne et al. (2016), involving charged sulfuric acid–water–ammonia nucleation, when coupled with organic growth of the nucleated particles, was most consistent with the observations for 5 of 32 cases. Similarly, the neutral sulfuric acid–water–ammonia method of Napari (2002), when scaled with a tuning factor and with organic growth added, was most consistent for 6 of 32 cases. We find that to best reproduce both nucleation and growth rates, the mixing ratios of gas-phase organic precursors generally need to be at least twice that of SO2, a proxy for dimethyl sulfide (DMS). Unfortunately, we have no information on the nature of oxidized organic species that participated in NPF in this region. Global models rarely include organic-driven nucleation and growth pathways in UT conditions where globally significant NPF takes place, which may result in poor estimates of NPF and CCN abundance and contribute to uncertainties in aerosol–cloud–radiation effects. Furthermore, our results indicate that the organic aerosol precursor vapors may be important in the tropical UT above marine regions, a finding that should guide future observational efforts.

During the first phase of the Biomass Burn Operational Project (BBOP) field campaign, conducted in the Pacific Northwest, the DOE G-1 aircraft was used to follow the time evolution of wildfire smoke from near the point of emission to locations 2–3.5 h downwind. In nine flights we made repeated transects of wildfire plumes at varying downwind distances and could thereby follow the plume's time evolution. On average there was little change in dilution-normalized aerosol mass concentration as a function of downwind distance. This consistency hides a dynamic system in which primary aerosol particles are evaporating and secondary ones condensing. Organic aerosol is oxidized as a result. On all transects more than 90 % of aerosol is organic. In freshly emitted smoke aerosol, NH4+ is approximately equivalent to NO3. After 2 h of daytime aging, NH4+ increased and is approximately equivalent to the sum of Cl, SO42, and NO3. Particle size increased with downwind distance, causing particles to be more efficient scatters. Averaged over nine flights, mass scattering efficiency (MSE) increased in ∼ 2 h by 56 % and doubled in one flight. Mechanisms for redistributing mass from small to large particles are discussed. Coagulation is effective at moving aerosol from the Aitken to accumulation modes but yields only a minor increase in MSE. As absorption remained nearly constant with age, the time evolution of single scatter albedo was controlled by age-dependent scattering. Near-fire aerosol had a single scatter albedo (SSA) of 0.8–0.9. After 1 to 2 h of aging SSAs were typically 0.9 and greater. Assuming global-average surface and atmospheric conditions, the observed age dependence in SSA would change the direct radiative effect of a wildfire plume from near zero near the fire to a cooling effect downwind.

Despite the potential importance of black carbon (BC) for radiative forcing of the Arctic atmosphere, vertically resolved measurements of the particle light scattering coefficient (σsp) and light absorption coefficient (σap) in the springtime Arctic atmosphere are infrequent, especially measurements at latitudes at or above 80∘ N. Here, relationships among vertically distributed aerosol optical properties (σap, σsp and single scattering albedo or SSA), particle microphysics and particle chemistry are examined for a region of the Canadian archipelago between 79.9 and 83.4∘ N from near the surface to 500 hPa. Airborne data collected during April 2015 are combined with ground-based observations from the observatory at Alert, Nunavut and simulations from the Goddard Earth Observing System (GEOS) model, GEOS-Chem, coupled with the TwO-Moment Aerosol Sectional (TOMAS) model (collectively GEOS-Chem–TOMAS; Kodros et al., 2018) to further our knowledge of the effects of BC on light absorption in the Arctic troposphere. The results are constrained for σsp less than 15 Mm−1, which represent 98 % of the observed σsp, because the single scattering albedo (SSA) has a tendency to be lower at lower σsp, resulting in a larger relative contribution to Arctic warming. At 18.4 m2 g−1, the average BC mass absorption coefficient (MAC) from the combined airborne and Alert observations is substantially higher than the two averaged modelled MAC values (13.6 and 9.1 m2 g−1) for two different internal mixing assumptions, the latter of which is based on previous observations. The higher observed MAC value may be explained by an underestimation of BC, the presence of small amounts of dust and/or possible differences in BC microphysics and morphologies between the observations and model. In comparing the observations and simulations, we present σap and SSA, as measured, and σap∕2 and the corresponding SSA to encompass the lower modelled MAC that is more consistent with accepted MAC values. Median values of the measured σap, rBC and the organic component of particles all increase by a factor of 1.8±0.1, going from near-surface to 750 hPa, and values higher than the surface persist to 600 hPa. Modelled BC, organics and σap agree with the near-surface measurements but do not reproduce the higher values observed between 900 and 600 hPa. The differences between modelled and observed optical properties follow the same trend as the differences between the modelled and observed concentrations of the carbonaceous components (black and organic). Model-observation discrepancies may be mostly due to the modelled ejection of biomass burning particles only into the boundary layer at the sources. For the assumption of the observed MAC value, the SSA range between 0.88 and 0.94, which is significantly lower than other recent estimates for the Arctic, in part reflecting the constraint of σsp Mm−1. The large uncertainties in measuring optical properties and BC, and the large differences between measured and modelled values here and in the literature, argue for improved measurements of BC and light absorption by BC and more vertical profiles of aerosol chemistry, microphysics and other optical properties in the Arctic.

Biomass burning is a major source of trace gases and aerosols that can ultimately impact health, air quality, and climate. Global and regional-scale three-dimensional Eulerian chemical transport models (CTMs) use estimates of the primary emissions from fires and can unphysically mix them across large-scale grid boxes, leading to incorrect estimates of the impact of biomass burning events. On the other hand, plume-scale process models allow for explicit simulation and examination of the chemical and physical transformations of trace gases and aerosols within biomass burning smoke plumes, and they may be used to develop parameterizations of this aging process for coarser grid-scale models. Here we describe the coupled SAM-ASP plume-scale process model, which consists of coupling the large-eddy simulation model, the System for Atmospheric Modelling (SAM), with the detailed gas and aerosol chemistry model, the Aerosol Simulation Program (ASP). We find that the SAM-ASP version 1.0 model is able to correctly simulate the dilution of CO in a California chaparral smoke plume, as well as the chemical loss of NOx, HONO, and NH3 within the plume, the formation of PAN and O3, the loss of OA, and the change in the size distribution of aerosols as compared to measurements and previous single-box model results. The newly coupled model is able to capture the cross-plume vertical and horizontal concentration gradients as the fire plume evolves downwind of the emission source. The integration and evaluation of SAM-ASP version 1.0 presented here will support the development of parameterizations of near-source biomass burning chemistry that can be used to more accurately simulate biomass burning chemical and physical transformations of trace gases and aerosols within coarser grid-scale CTMs.

The spatial distribution and properties of submicron organic aerosol (OA) are among the key sources of uncertainty in our understanding of aerosol effects on climate. Uncertainties are particularly large over remote regions of the free troposphere and Southern Ocean, where very few data have been available and where OA predictions from AeroCom Phase II global models span 2 to 3 orders of magnitude, greatly exceeding the model spread over source regions. The (nearly) pole-to-pole vertical distribution of non-refractory aerosols was measured with an aerosol mass spectrometer onboard the NASA DC-8 aircraft as part of the Atmospheric Tomography (ATom) mission during the Northern Hemisphere summer (August 2016) and winter (February 2017). This study presents the first extensive characterization of OA mass concentrations and their level of oxidation in the remote atmosphere. OA and sulfate are the major contributors by mass to submicron aerosols in the remote troposphere, together with sea salt in the marine boundary layer. Sulfate was dominant in the lower stratosphere. OA concentrations have a strong seasonal and zonal variability, with the highest levels measured in the lower troposphere in the summer and over the regions influenced by biomass burning from Africa (up to 10 µg sm−3). Lower concentrations (∼0.1–0.3 µg sm−3) are observed in the northern middle and high latitudes and very low concentrations ( µg sm−3) in the southern middle and high latitudes. The ATom dataset is used to evaluate predictions of eight current global chemistry models that implement a variety of commonly used representations of OA sources and chemistry, as well as of the AeroCom-II ensemble. The current model ensemble captures the average vertical and spatial distribution of measured OA concentrations, and the spread of the individual models remains within a factor of 5. These results are significantly improved over the AeroCom-II model ensemble, which shows large overestimations over these regions. However, some of the improved agreement with observations occurs for the wrong reasons, as models have the tendency to greatly overestimate the primary OA fraction and underestimate the secondary fraction. Measured OA in the remote free troposphere is highly oxygenated, with organic aerosol to organic carbon (OA ∕ OC) ratios of ∼2.2–2.8, and is 30 %–60 % more oxygenated than in current models, which can lead to significant errors in OA concentrations. The model–measurement comparisons presented here support the concept of a more dynamic OA system as proposed by Hodzic et al. (2016), with enhanced removal of primary OA and a stronger production of secondary OA in global models needed to provide better agreement with observations.

Chemical transport models have historically struggled to accurately simulate the magnitude and variability of observed organic aerosol (OA), with previous studies demonstrating that models significantly underestimate observed concentrations in the troposphere. In this study, we explore two different model OA schemes within the standard GEOS-Chem chemical transport model and evaluate the simulations against a suite of 15 globally distributed airborne campaigns from 2008 to 2017, primarily in the spring and summer seasons. These include the ATom, KORUS-AQ, GoAmazon, FRAPPE, SEAC4RS, SENEX, DC3, CalNex, OP3, EUCAARI, ARCTAS and ARCPAC campaigns and provide broad coverage over a diverse set of atmospheric composition regimes – anthropogenic, biogenic, pyrogenic and remote. The schemes include significant differences in their treatment of the primary and secondary components of OA – a “simple scheme” that models primary OA (POA) as non-volatile and takes a fixed-yield approach to secondary OA (SOA) formation and a “complex scheme” that simulates POA as semi-volatile and uses a more sophisticated volatility basis set approach for non-isoprene SOA, with an explicit aqueous uptake mechanism to model isoprene SOA. Despite these substantial differences, both the simple and complex schemes perform comparably across the aggregate dataset in their ability to capture the observed variability (with an R2 of 0.41 and 0.44, respectively). The simple scheme displays greater skill in minimizing the overall model bias (with a normalized mean bias of 0.04 compared to 0.30 for the complex scheme). Across both schemes, the model skill in reproducing observed OA is superior to previous model evaluations and approaches the fidelity of the sulfate simulation within the GEOS-Chem model. However, there are significant differences in model performance across different chemical source regimes, classified here into seven categories. Higher-resolution nested regional simulations indicate that model resolution is an important factor in capturing variability in highly localized campaigns, while also demonstrating the importance of well-constrained emissions inventories and local meteorology, particularly over Asia. Our analysis suggests that a semi-volatile treatment of POA is superior to a non-volatile treatment. It is also likely that the complex scheme parameterization overestimates biogenic SOA at the global scale. While this study identifies factors within the SOA schemes that likely contribute to OA model bias (such as a strong dependency of the bias in the complex scheme on relative humidity and sulfate concentrations), comparisons with the skill of the sulfate aerosol scheme in GEOS-Chem indicate the importance of other drivers of bias, such as emissions, transport and deposition, that are exogenous to the OA chemical scheme.

A pilot field campaign was conducted in the fall and winter of 2017 in northern Colorado to test the deployment of the Aerosol Mass and Optical Depth (AMOD) instrument as part of the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) network. Citizen scientists were recruited to set up the device to take filter and optical measurements of aerosols in their backyards. The goal of the network is to provide more surface particulate matter and aerosol optical depth (AOD) measurements to increase the spatial and temporal resolution of ratios of fine particulate matter (PM2.5) to AOD and to improve satellite-based estimates of air quality. Participants collected 65 filters and 160 multi-wavelength AOD measurements, from which 109 successful PM2.5 : AOD ratios were calculated. We show that PM2.5, AOD, and their ratio (PM2.5 : AOD) often vary substantially over relatively short spatial scales; this spatial variation is not typically resolved by satellite- and model-based PM2.5 exposure estimates. The success of the pilot campaign suggests that citizen-science networks are a viable means for providing new insight into surface air quality. We also discuss lessons learned and AMOD design modifications, which will be used in future wider deployments of the CEAMS network.

Globally, fine particulate matter (PM2.5) air pollution is a leading contributor to death, disease, and environmental degradation. Satellite-based measurements of aerosol optical depth (AOD) are used to estimate PM2.5 concentrations across the world, but the relationship between satellite-estimated AOD and ground-level PM2.5 is uncertain. Sun photometers measure AOD from the Earth's surface and are often used to improve satellite data; however, reference-grade photometers and PM2.5 monitors are expensive and rarely co-located. This work presents the development and validation of the aerosol mass and optical depth (AMOD) sampler, an inexpensive and compact device that simultaneously measures PM2.5 mass and AOD. The AMOD utilizes a low-cost light-scattering sensor in combination with a gravimetric filter measurement to quantify ground-level PM2.5. Aerosol optical depth is measured using optically filtered photodiodes at four discrete wavelengths. Field validation studies revealed agreement within 10 % for AOD values measured between co-located AMOD and AErosol RObotics NETwork (AERONET) monitors and for PM2.5 mass measured between co-located AMOD and EPA Federal Equivalent Method (FEM) monitors. These results demonstrate that the AMOD can quantify AOD and PM2.5 accurately at a fraction of the cost of existing reference monitors.

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of −24 % and −35 % for particles with dry diameters >50 and >120 nm, as well as −36 % and −34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations ( %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB −13 % and −22 % for updraft velocities 0.3 and 0.6 m s−1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (∂Nd/∂Na) and to updraft velocity (∂Nd/∂w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities ∂Nd/∂Na and ∂Nd/∂w; models may be predisposed to be too “aerosol sensitive” or “aerosol insensitive” in aerosol–cloud–climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain inter-model biases on the aerosol indirect effect.

Biomass burning is a significant global source of aerosol number and mass. In fresh biomass burning plumes, aerosol coagulation reduces aerosol number and increases the median size of aerosol size distributions, impacting aerosol radiative effects. Near-source biomass burning aerosol coagulation occurs at spatial scales much smaller than the grid boxes of global and many regional models. To date, these models have ignored sub-grid coagulation and instantly mixed fresh biomass burning emissions into coarse grid boxes. A previous study found that the rate of particle growth by coagulation within an individual smoke plume can be approximated using the aerosol mass emissions rate, initial size distribution median diameter and modal width, plume mixing depth, and wind speed. In this paper, we use this parameterization of sub-grid coagulation in the GEOS-Chem–TOMAS (TwO-Moment Aerosol Sectional) global aerosol microphysics model to quantify the impacts on global aerosol size distributions, the direct radiative effect, and the cloud-albedo aerosol indirect effect. We find that inclusion of biomass burning sub-grid coagulation reduces the biomass burning impact on the number concentration of particles larger than 80 nm (a proxy for CCN-sized particles) by 37 % globally. This cloud condensation nuclei (CCN) reduction causes our estimated global biomass burning cloud-albedo aerosol indirect effect to decrease from −76 to −43 mW m−2. Further, as sub-grid coagulation moves mass to sizes with more efficient scattering, including it increases our estimated biomass burning all-sky direct effect from −224 to −231 mW m−2, with assumed external mixing of black carbon and from −188 to −197 mW m−2 and with assumed internal mixing of black carbon with core-shell morphology. However, due to differences in fire and meteorological conditions across regions, the impact of sub-grid coagulation is not globally uniform. We also test the sensitivity of the impact of sub-grid coagulation to two different biomass burning emission inventories to various assumptions about the fresh biomass burning aerosol size distribution and to two different timescales of sub-grid coagulation. The impacts of sub-grid coagulation are qualitatively the same regardless of these assumptions.

Summertime Arctic aerosol size distributions are strongly controlled by natural regional emissions. Within this context, we use a chemical transport model with size-resolved aerosol microphysics (GEOS-Chem-TOMAS) to interpret measurements of aerosol size distributions from the Canadian Arctic Archipelago during the summer of 2016, as part of the “NETwork on Climate and Aerosols: Addressing key uncertainties in Remote Canadian Environments” (NETCARE) project. Our simulations suggest that condensation of secondary organic aerosol (SOA) from precursor vapors emitted in the Arctic and near Arctic marine (ice-free seawater) regions plays a key role in particle growth events that shape the aerosol size distributions observed at Alert (82.5∘ N, 62.3∘ W), Eureka (80.1∘ N, 86.4∘ W), and along a NETCARE ship track within the Archipelago. We refer to this SOA as Arctic marine SOA (AMSOA) to reflect the Arctic marine-based and likely biogenic sources for the precursors of the condensing organic vapors. AMSOA from a simulated flux (500 µgm-2day-1, north of 50∘ N) of precursor vapors (with an assumed yield of unity) reduces the summertime particle size distribution model–observation mean fractional error 2- to 4-fold, relative to a simulation without this AMSOA. Particle growth due to the condensable organic vapor flux contributes strongly (30 %–50 %) to the simulated summertime-mean number of particles with diameters larger than 20 nm in the study region. This growth couples with ternary particle nucleation (sulfuric acid, ammonia, and water vapor) and biogenic sulfate condensation to account for more than 90 % of this simulated particle number, which represents a strong biogenic influence. The simulated fit to summertime size-distribution observations is further improved at Eureka and for the ship track by scaling up the nucleation rate by a factor of 100 to account for other particle precursors such as gas-phase iodine and/or amines and/or fragmenting primary particles that could be missing from our simulations. Additionally, the fits to the observed size distributions and total aerosol number concentrations for particles larger than 4 nm improve with the assumption that the AMSOA contains semi-volatile species: the model–observation mean fractional error is reduced 2- to 3-fold for the Alert and ship track size distributions. AMSOA accounts for about half of the simulated particle surface area and volume distributions in the summertime Canadian Arctic Archipelago, with climate-relevant simulated summertime pan-Arctic-mean top-of-the-atmosphere aerosol direct (−0.04 W m−2) and cloud-albedo indirect (−0.4 W m−2) radiative effects, which due to uncertainties are viewed as an order of magnitude estimate. Future work should focus on further understanding summertime Arctic sources of AMSOA.

Atmospheric marine aerosol particles impact Earth's albedo and climate. These particles can be primary or secondary and come from a variety of sources, including sea salt, dissolved organic matter, volatile organic compounds, and sulfur-containing compounds. Dimethylsulfide (DMS) marine emissions contribute greatly to the global biogenic sulfur budget, and its oxidation products can contribute to aerosol mass, specifically as sulfuric acid and methanesulfonic acid (MSA). Further, sulfuric acid is a known nucleating compound, and MSA may be able to participate in nucleation when bases are available. As DMS emissions, and thus MSA and sulfuric acid from DMS oxidation, may have changed since pre-industrial times and may change in a warming climate, it is important to characterize and constrain the climate impacts of both species. Currently, global models that simulate aerosol size distributions include contributions of sulfate and sulfuric acid from DMS oxidation, but to our knowledge, global models typically neglect the impact of MSA on size distributions. In this study, we use the GEOS-Chem-TOMAS (GC-TOMAS) global aerosol microphysics model to determine the impact on aerosol size distributions and subsequent aerosol radiative effects from including MSA in the size-resolved portion of the model. The effective equilibrium vapor pressure of MSA is currently uncertain, and we use the Extended Aerosol Inorganics Model (E-AIM) to build a parameterization for GC-TOMAS of MSA's effective volatility as a function of temperature, relative humidity, and available gas-phase bases, allowing MSA to condense as an ideally nonvolatile or semivolatile species or too volatile to condense. We also present two limiting cases for MSA's volatility, assuming that MSA is always ideally nonvolatile (irreversible condensation) or that MSA is always ideally semivolatile (quasi-equilibrium condensation but still irreversible condensation). We further present simulations in which MSA participates in binary and ternary nucleation with the same efficacy as sulfuric acid whenever MSA is treated as ideally nonvolatile. When using the volatility parameterization described above (both with and without nucleation), including MSA in the model changes the global annual averages at 900 hPa of submicron aerosol mass by 1.2 %, N3 (number concentration of particles greater than 3 nm in diameter) by −3.9 % (non-nucleating) or 112.5 % (nucleating), N80 by 0.8 % (non-nucleating) or 2.1 % (nucleating), the cloud-albedo aerosol indirect effect (AIE) by −8.6 mW m−2 (non-nucleating) or −26 mW m−2 (nucleating), and the direct radiative effect (DRE) by −15 mW m−2 (non-nucleating) or −14 mW m−2 (nucleating). The sulfate and sulfuric acid from DMS oxidation produces 4–6 times more submicron mass than MSA does, leading to an ∼10 times stronger cooling effect in the DRE. But the changes in N80 are comparable between the contributions from MSA and from DMS-derived sulfate/sulfuric acid, leading to comparable changes in the cloud-albedo AIE. Model–measurement comparisons with the Heintzenberg et al. (2000) dataset over the Southern Ocean indicate that the default model has a missing source or sources of ultrafine particles: the cases in which MSA participates in nucleation (thus increasing ultrafine number) most closely match the Heintzenberg distributions, but we cannot conclude nucleation from MSA is the correct reason for improvement. Model–measurement comparisons with particle-phase MSA observed with a customized Aerodyne high-resolution time-of-flight aerosol mass spectrometer (AMS) from the ATom campaign show that cases with the MSA volatility parameterizations (both with and without nucleation) tend to fit the measurements the best (as this is the first use of MSA measurements from ATom, we provide a detailed description of these measurements and their calibration). However, no one model sensitivity case shows the best model–measurement agreement for both Heintzenberg and the ATom campaigns. As there are uncertainties in both MSA's behavior (nucleation and condensation) and the DMS emissions inventory, further studies on both fronts are needed to better constrain MSA's past, current, and future impacts upon the global aerosol size distribution and radiative forcing.

Motivated by the need to predict how the Arctic atmosphere will change in a warming world, this article summarizes recent advances made by the research consortium NETCARE (Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments) that contribute to our fundamental understanding of Arctic aerosol particles as they relate to climate forcing. The overall goal of NETCARE research has been to use an interdisciplinary approach encompassing extensive field observations and a range of chemical transport, earth system, and biogeochemical models. Several major findings and advances have emerged from NETCARE since its formation in 2013. (1) Unexpectedly high summertime dimethyl sulfide (DMS) levels were identified in ocean water (up to 75 nM) and the overlying atmosphere (up to 1 ppbv) in the Canadian Arctic Archipelago (CAA). Furthermore, melt ponds, which are widely prevalent, were identified as an important DMS source (with DMS concentrations of up to 6 nM and a potential contribution to atmospheric DMS of 20 % in the study area). (2) Evidence of widespread particle nucleation and growth in the marine boundary layer was found in the CAA in the summertime, with these events observed on 41 % of days in a 2016 cruise. As well, at Alert, Nunavut, particles that are newly formed and grown under conditions of minimal anthropogenic influence during the months of July and August are estimated to contribute 20 % to 80 % of the 30–50 nm particle number density. DMS-oxidation-driven nucleation is facilitated by the presence of atmospheric ammonia arising from seabird-colony emissions, and potentially also from coastal regions, tundra, and biomass burning. Via accumulation of secondary organic aerosol (SOA), a significant fraction of the new particles grow to sizes that are active in cloud droplet formation. Although the gaseous precursors to Arctic marine SOA remain poorly defined, the measured levels of common continental SOA precursors (isoprene and monoterpenes) were low, whereas elevated mixing ratios of oxygenated volatile organic compounds (OVOCs) were inferred to arise via processes involving the sea surface microlayer. (3) The variability in the vertical distribution of black carbon (BC) under both springtime Arctic haze and more pristine summertime aerosol conditions was observed. Measured particle size distributions and mixing states were used to constrain, for the first time, calculations of aerosol–climate interactions under Arctic conditions. Aircraft- and ground-based measurements were used to better establish the BC source regions that supply the Arctic via long-range transport mechanisms, with evidence for a dominant springtime contribution from eastern and southern Asia to the middle troposphere, and a major contribution from northern Asia to the surface. (4) Measurements of ice nucleating particles (INPs) in the Arctic indicate that a major source of these particles is mineral dust, likely derived from local sources in the summer and long-range transport in the spring. In addition, INPs are abundant in the sea surface microlayer in the Arctic, and possibly play a role in ice nucleation in the atmosphere when mineral dust concentrations are low. (5) Amongst multiple aerosol components, BC was observed to have the smallest effective deposition velocities to high Arctic snow (0.03 cm s−1).

The interaction of particles with the chamber walls has been a significant source of uncertainty when analyzing results of secondary organic aerosol (SOA) formation experiments performed in Teflon chambers. A number of particle wall-loss correction methods have been proposed including the use of a size-independent loss rate constant, the ratio of suspended organic mass to that of a conserved tracer (e.g., sulfate seeds), and a size-dependent loss rate constant, etc. For complex experiments such as the chemical aging of SOA, the results of the SOA quantification analysis can be quite sensitive to the adopted correction method due to the evolution of the particle size distribution and the duration of these experiments. We evaluated the performance of several particle wall-loss correction methods for aging experiments of α-pinene ozonolysis products. Determining the loss rates from seed loss periods is necessary for this system because it is not clear when chemical reactions have been completed. Results from the OA ∕ sulfate ratio and the size-independent correction methods can be influenced significantly by the size dependence of the particle wall-loss process. Coagulation can also affect the particle size distribution, especially for particles with diameter less than 100 nm, thus introducing errors in the results of the wall-loss correction. The corresponding loss rate constants may vary from experiment to experiment, and even during a specific experiment. Friction between the Teflon chamber walls and non-conductive surfaces can significantly increase particle wall-loss rates and the chamber may require weeks to recover to its original condition. Experimental procedures are proposed for the characterization of particle losses during different stages of these experiments and the evaluation of corresponding particle wall-loss correction.

Abstract Human exposure to airborne particulate matter (PM) increases the risk of negative health outcomes; however, substantial uncertainty remains in quantifying these exposure‐response relationships. In particular, relating increased risk of mortality to exposure to PM with diameters smaller than 2.5 μm (PM2.5) neglects variability in the underlying size distribution of PM2.5 exposure and size‐resolved deposition in human airways. In this study, we combine a size‐resolved respiratory particle‐deposition model with a global size‐resolved aerosol model to estimate the variability in particle deposition along the respiratory tract due to variability in ambient PM size distributions. We find that the ratio of deposited PM mass in the tracheobronchial and alveolar regions per unit ambient PM2.5 exposure (deposition ratio and DRTB + AV) varies by 20–30% between populated regions due to variability in ambient PM size distributions. Furthermore, DRTB + AV can vary by as high as a factor of 4 between the fossil‐fuel‐dominated region of the Eastern United States and the desert‐dust‐dominated region of North Africa. When considering individual PM species, such as sulfate or organic matter, we still find variability in the DRTB + AV on the order of 30% due to regional variability in the size distribution. Finally, the spatial distribution of DRTB + AV based on number or surface area is substantially different than the DRTB + AV based on mass. These results suggest that regional variability in ambient aerosol size distributions drive variability in PM deposition in the body, which may lead to variability in the health response from exposure to PM2.5.

Transport of anthropogenic aerosol into the Arctic in the spring months has the potential to affect regional climate; however, modeling estimates of the aerosol direct radiative effect (DRE) are sensitive to uncertainties in the mixing state of black carbon (BC). A common approach in previous modeling studies is to assume an entirely external mixture (all primarily scattering species are in separate particles from BC) or internal mixture (all primarily scattering species are mixed in the same particles as BC). To provide constraints on the size-resolved mixing state of BC, we use airborne single-particle soot photometer (SP2) and ultrahigh-sensitivity aerosol spectrometer (UHSAS) measurements from the Alfred Wegener Institute (AWI) Polar 6 flights from the NETCARE/PAMARCMIP2015 campaign to estimate coating thickness as a function of refractory BC (rBC) core diameter and the fraction of particles containing rBC in the springtime Canadian high Arctic. For rBC core diameters in the range of 140 to 220 nm, we find average coating thicknesses of approximately 45 to 40 nm, respectively, resulting in ratios of total particle diameter to rBC core diameters ranging from 1.6 to 1.4. For total particle diameters ranging from 175 to 730 nm, rBC-containing particle number fractions range from 16 % to 3 %, respectively. We combine the observed mixing-state constraints with simulated size-resolved aerosol mass and number distributions from GEOS-Chem–TOMAS to estimate the DRE with observed bounds on mixing state as opposed to assuming an entirely external or internal mixture. We find that the pan-Arctic average springtime DRE ranges from −1.65 to −1.34 W m−2 when assuming entirely externally or internally mixed BC. This range in DRE is reduced by over a factor of 2 (−1.59 to −1.45 W m−2) when using the observed mixing-state constraints. The difference in DRE between the two observed mixing-state constraints is due to an underestimation of BC mass fraction in the springtime Arctic in GEOS-Chem–TOMAS compared to Polar 6 observations. Measurements of mixing state provide important constraints for model estimates of DRE.

Abstract Fine particulate matter (PM2.5) from U.S. anthropogenic sources is decreasing. However, previous studies have predicted that PM2.5 emissions from wildfires will increase in the midcentury to next century, potentially offsetting improvements gained by continued reductions in anthropogenic emissions. Therefore, some regions could experience worse air quality, degraded visibility, and increases in population‐level exposure. We use global climate model simulations to estimate the impacts of changing fire emissions on air quality, visibility, and premature deaths in the middle and late 21st century. We find that PM2.5 concentrations will decrease overall in the contiguous United States (CONUS) due to decreasing anthropogenic emissions (total PM2.5 decreases by 3% in Representative Concentration Pathway [RCP] 8.5 and 34% in RCP4.5 by 2100), but increasing fire‐related PM2.5 (fire‐related PM2.5 increases by 55% in RCP4.5 and 190% in RCP8.5 by 2100) offsets these benefits and causes increases in total PM2.5 in some regions. We predict that the average visibility will improve across the CONUS, but fire‐related PM2.5 will reduce visibility on the worst days in western and southeastern U.S. regions. We estimate that the number of deaths attributable to total PM2.5 will decrease in both the RCP4.5 and RCP8.5 scenarios (from 6% to 4–5%), but the absolute number of premature deaths attributable to fire‐related PM2.5 will double compared to early 21st century. We provide the first estimates of future smoke health and visibility impacts using a prognostic land‐fire model. Our results suggest the importance of using realistic fire emissions in future air quality projections.

Oxidation flow reactors (OFRs) allow the concentration of a given atmospheric oxidant to be increased beyond ambient levels in order to study secondary organic aerosol (SOA) formation and aging over varying periods of equivalent aging by that oxidant. Previous studies have used these reactors to determine the bulk OA mass and chemical evolution. To our knowledge, no OFR study has focused on the interpretation of the evolving aerosol size distributions. In this study, we use size-distribution measurements of the OFR and an aerosol microphysics model to learn about size-dependent processes in the OFR. Specifically, we use OFR exposures between 0.09 and 0.9 equivalent days of OH aging from the 2011 BEACHON-RoMBAS and GoAmazon2014/5 field campaigns. We use simulations in the TOMAS (TwO-Moment Aerosol Sectional) microphysics box model to constrain the following parameters in the OFR: (1) the rate constant of gas-phase functionalization reactions of organic compounds with OH, (2) the rate constant of gas-phase fragmentation reactions of organic compounds with OH, (3) the reactive uptake coefficient for heterogeneous fragmentation reactions with OH, (4) the nucleation rate constants for three different nucleation schemes, and (5) an effective accommodation coefficient that accounts for possible particle diffusion limitations of particles larger than 60 nm in diameter.We find the best model-to-measurement agreement when the accommodation coefficient of the larger particles (Dp > 60 nm) was 0.1 or lower (with an accommodation coefficient of 1 for smaller particles), which suggests a diffusion limitation in the larger particles. When using these low accommodation-coefficient values, the model agrees with measurements when using a published H2SO4-organics nucleation mechanism and previously published values of rate constants for gas-phase oxidation reactions. Further, gas-phase fragmentation was found to have a significant impact upon the size distribution, and including fragmentation was necessary for accurately simulating the distributions in the OFR. The model was insensitive to the value of the reactive uptake coefficient on these aging timescales. Monoterpenes and isoprene could explain 24 %–95 % of the observed change in total volume of aerosol in the OFR, with ambient semivolatile and intermediate-volatility organic compounds (S/IVOCs) appearing to explain the remainder of the change in total volume. These results provide support to the mass-based findings of previous OFR studies, give insight to important size-distribution dynamics in the OFR, and enable the design of future OFR studies focused on new particle formation and/or microphysical processes.

Abstract While there have been substantial efforts to quantify the health burden of exposure to PM2.5 from solid fuel use (SFU), the sensitivity of mortality estimates to uncertainties in input parameters has not been quantified. Moreover, previous studies separate mortality from household and ambient air pollution. In this study, we develop a new estimate of mortality attributable to SFU due to the joint exposure from household and ambient PM2.5 pollution and perform a variance‐based sensitivity analysis on mortality attributable to SFU. In the joint exposure calculation, we estimate 2.81 (95% confidence interval: 2.48–3.28) million premature deaths in 2015 attributed to PM2.5 from SFU, which is 580,000 (18%) fewer deaths than would be calculated by summing separate household and ambient mortality calculations. Regarding the sources of uncertainties in these estimates, in China, India, and Latin America, we find that 53–56% of the uncertainty in mortality attributable to SFU is due to uncertainty in the percent of the population using solid fuels and 42–50% from the concentration‐response function. In sub‐Saharan Africa, baseline mortality rate (72%) and the concentration‐response function (33%) dominate the uncertainty space. Conversely, the sum of the variance contributed by ambient and household PM2.5 exposure ranges between 15 and 38% across all regions (the percentages do not sum to 100% as some uncertainty is shared between parameters). Our findings suggest that future studies should focus on more precise quantification of solid fuel use and the concentration‐response relationship to PM2.5, as well as mortality rates in Africa.

Most prior field studies of new particle formation (NPF) have been performed at or near ground level, leaving many unanswered questions regarding the vertical extent of NPF. To address this, we measured concentrations of 11–16 nm diameter particles from ground level to 1000 m during the 2013 New Particle Formation Study at the Atmospheric Radiation Measurement Southern Great Plains site in Lamont, Oklahoma. The measurements were performed using a tethered balloon carrying two condensation particle counters that were configured for two different particle cut-off diameters. These observations were compared to data from three scanning mobility particle sizers at the ground level. We observed that 11–16 nm diameter particles were generated at the top region of the boundary layer, and were then rapidly mixed throughout the boundary layer. We also estimate liquid water content of nanoparticles using ground-based measurements of particle hygroscopicity obtained with a Humidified Tandem Differential Mobility Analyzer and vertically resolved relative humidity (RH) and temperature measured with a Raman lidar. Our analyses of these observations lead to the following conclusions regarding nanoparticles formed during NPF events at this site: (1) ground-based observations may not always accurately represent the timing, distribution, and meteorological conditions associated with the onset of NPF; (2) nanoparticles are highly hygroscopic and typically contain up to 50 % water by volume, and during conditions of high RH combined with high particle hygroscopicity, particles can be up to 95 % water by volume; (3) increased liquid water content of nanoparticles at high RH greatly enhances the partitioning of water-soluble species like organic acids into ambient nanoparticles.

Vertical distributions of atmospheric dimethyl sulfide (DMS(g)) were sampled aboard the research aircraft Polar 6 near Lancaster Sound, Nunavut, Canada, in July 2014 and on pan-Arctic flights in April 2015 that started from Longyearbyen, Spitzbergen, and passed through Alert and Eureka, Nunavut, and Inuvik, Northwest Territories. Larger mean DMS(g) mixing ratios were present during April 2015 (campaign mean of 116 ± 8 pptv) compared to July 2014 (campaign mean of 20 ± 6 pptv). During July 2014, the largest mixing ratios were found near the surface over the ice edge and open water. DMS(g) mixing ratios decreased with altitude up to about 3 km. During April 2015, profiles of DMS(g) were more uniform with height and some profiles showed an increase with altitude. DMS reached as high as 100 pptv near 2500 m. Relative to the observation averages, GEOS-Chem (www.geos-chem.org) chemical transport model simulations were higher during July and lower during April. Based on the simulations, more than 90 % of the July DMS(g) below 2 km and more than 90 % of the April DMS(g) originated from Arctic seawater (north of 66° N). During April, 60 % of the DMS(g), between 500 and 3000 m originated from Arctic seawater. During July 2014, FLEXPART (FLEXible PARTicle dispersion model) simulations locate the sampled air mass over Baffin Bay and the Canadian Arctic Archipelago 4 days back from the observations. During April 2015, the locations of the air masses 4 days back from sampling were varied: Baffin Bay/Canadian Archipelago, the Arctic Ocean, Greenland and the Pacific Ocean. Our results highlight the role of open water below the flight as the source of DMS(g) during July 2014 and the influence of long-range transport (LRT) of DMS(g) from further afield in the Arctic above 2500 m during April 2015.

Exposure to wildland fire smoke is associated with negative effects on human health. However, these effects are poorly quantified. Accurately attributing health endpoints to wildland fire smoke requires determining the locations, concentrations, and durations of smoke events. Most current methods for assessing these smoke events (ground-based measurements, satellite observations, and chemical transport modeling) are limited temporally, spatially, and/or by their level of accuracy. In this work, we explore using daily social media posts from Facebook regarding smoke, haze, and air quality to assess population-level exposure for the summer of 2015 in the western US. We compare this de-identified, aggregated Facebook dataset to several other datasets that are commonly used for estimating exposure, such as satellite observations (MODIS aerosol optical depth and Hazard Mapping System smoke plumes), daily (24 h) average surface particulate matter measurements, and model-simulated (WRF-Chem) surface concentrations. After adding population-weighted spatial smoothing to the Facebook data, this dataset is well correlated (R2 generally above 0.5) with the other methods in smoke-impacted regions. The Facebook dataset is better correlated with surface measurements of PM2. 5 at a majority of monitoring sites (163 of 293 sites) than the satellite observations and our model simulation. We also present an example case for Washington state in 2015, for which we combine this Facebook dataset with MODIS observations and WRF-Chem-simulated PM2. 5 in a regression model. We show that the addition of the Facebook data improves the regression model's ability to predict surface concentrations. This high correlation of the Facebook data with surface monitors and our Washington state example suggests that this social-media-based proxy can be used to estimate smoke exposure in locations without direct ground-based particulate matter measurements.

Secondary organic aerosol (SOA) has been shown to form in biomass-burning emissions in laboratory and field studies. However, there is significant variability among studies in mass enhancement, which could be due to differences in fuels, fire conditions, dilution, and/or limitations of laboratory experiments and observations. This study focuses on understanding processes affecting biomass-burning SOA formation in laboratory smog-chamber experiments and in ambient plumes. Vapor wall losses have been demonstrated to be an important factor that can suppress SOA formation in laboratory studies of traditional SOA precursors; however, impacts of vapor wall losses on biomass-burning SOA have not yet been investigated. We use an aerosol-microphysical model that includes representations of volatility and oxidation chemistry to estimate the influence of vapor wall loss on SOA formation observed in the FLAME III smog-chamber studies. Our simulations with base-case assumptions for chemistry and wall loss predict a mean OA mass enhancement (the ratio of final to initial OA mass, corrected for particle-phase wall losses) of 1.8 across all experiments when vapor wall losses are modeled, roughly matching the mean observed enhancement during FLAME III. The mean OA enhancement increases to over 3 when vapor wall losses are turned off, implying that vapor wall losses reduce the apparent SOA formation. We find that this decrease in the apparent SOA formation due to vapor wall losses is robust across the ranges of uncertainties in the key model assumptions for wall-loss and mass-transfer coefficients and chemical mechanisms.We then apply similar assumptions regarding SOA formation chemistry and physics to smoke emitted into the atmosphere. In ambient plumes, the plume dilution rate impacts the organic partitioning between the gas and particle phases, which may impact the potential for SOA to form as well as the rate of SOA formation. We add Gaussian dispersion to our aerosol-microphysical model to estimate how SOA formation may vary under different ambient-plume conditions (e.g., fire size, emission mass flux, atmospheric stability). Smoke from small fires, such as typical prescribed burns, dilutes rapidly, which drives evaporation of organic vapor from the particle phase, leading to more effective SOA formation. Emissions from large fires, such as intense wildfires, dilute slowly, suppressing OA evaporation and subsequent SOA formation in the near field. We also demonstrate that different approaches to the calculation of OA enhancement in ambient plumes can lead to different conclusions regarding SOA formation. OA mass enhancement ratios of around 1 calculated using an inert tracer, such as black carbon or CO, have traditionally been interpreted as exhibiting little or no SOA formation; however, we show that SOA formation may have greatly contributed to the mass in these plumes.In comparison of laboratory and plume results, the possible inconsistency of OA enhancement between them could be in part attributed to the effect of chamber walls and plume dilution. Our results highlight that laboratory and field experiments that focus on the fuel and fire conditions also need to consider the effects of plume dilution or vapor losses to walls.

The effect of vapor-wall deposition on secondary organic aerosol (SOA) formation has gained significant attention; however, uncertainties in experimentally derived SOA mass yields due to uncertainties in particle-wall deposition remain. Different approaches have been used to correct for particle-wall deposition in SOA formation studies, each having its own set of assumptions in determining the particle-wall loss rate. In volatile and intermediate-volatility organic compound (VOC and IVOC) systems in which SOA formation is governed by kinetically limited growth, the effect of vapor-wall deposition on SOA mass yields can be constrained by using high surface area concentrations of seed aerosol to promote the condensation of SOA-forming vapors onto seed aerosol instead of the chamber walls. However, under such high seed aerosol levels, the presence of significant coagulation may complicate the particle-wall deposition correction. Here, we present a model framework that accounts for coagulation in chamber studies in which high seed aerosol surface area concentrations are used. For the α-pinene ozonolysis system, we find that after accounting for coagulation, SOA mass yields remain approximately constant when high seed aerosol surface area concentrations ( ≥ 8000 µm2 cm−3) are used, consistent with our prior study (Nah et al., 2016) showing that α-pinene ozonolysis SOA formation is governed by quasi-equilibrium growth. In addition, we systematically assess the uncertainties in the calculated SOA mass concentrations and yields between four different particle-wall loss correction methods over the series of α-pinene ozonolysis experiments. At low seed aerosol surface area concentrations (2 cm−3), the SOA mass yields at peak SOA growth obtained from the particle-wall loss correction methods agree within 14 %. However, at high seed aerosol surface area concentrations ( ≥ 8000 µm2 cm−3), the SOA mass yields at peak SOA growth obtained from different particle-wall loss correction methods can differ by as much as 58 %. These differences arise from assumptions made in the particle-wall loss correction regarding the first-order particle-wall loss rate. This study highlights the importance of accounting for particle-wall deposition accurately during SOA formation chamber experiments and assessing the uncertainties associated with the application of the particle-wall deposition correction method when comparing and using SOA mass yields measured in different studies.

The climatic impact of ammonia emissions from Arctic seabird-colony guano is poorly understood. Here, using observations and a chemical transport model, Croftet al. illustrate that guano-associated particles promote cloud-droplet formation, resulting in a pan-Arctic cooling tendency of approximately −0.5 W m−2.

New-particle formation (NPF) is a significant source of aerosol particles into the atmosphere. However, these particles are initially too small to have climatic importance and must grow, primarily through net uptake of low-volatility species, from diameters ∼ 1 to 30–100 nm in order to potentially impact climate. There are currently uncertainties in the physical and chemical processes associated with the growth of these freshly formed particles that lead to uncertainties in aerosol-climate modeling. Four main pathways for new-particle growth have been identified: condensation of sulfuric-acid vapor (and associated bases when available), condensation of organic vapors, uptake of organic acids through acid–base chemistry in the particle phase, and accretion of organic molecules in the particle phase to create a lower-volatility compound that then contributes to the aerosol mass. The relative importance of each pathway is uncertain and is the focus of this work. The 2013 New Particle Formation Study (NPFS) measurement campaign took place at the DOE Southern Great Plains (SGP) facility in Lamont, Oklahoma, during spring 2013. Measured gas- and particle-phase compositions during these new-particle growth events suggest three distinct growth pathways: (1) growth by primarily organics, (2) growth by primarily sulfuric acid and ammonia, and (3) growth by primarily sulfuric acid and associated bases and organics. To supplement the measurements, we used the particle growth model MABNAG (Model for Acid–Base chemistry in NAnoparticle Growth) to gain further insight into the growth processes on these 3 days at SGP. MABNAG simulates growth from (1) sulfuric-acid condensation (and subsequent salt formation with ammonia or amines), (2) near-irreversible condensation from nonreactive extremely low-volatility organic compounds (ELVOCs), and (3) organic-acid condensation and subsequent salt formation with ammonia or amines. MABNAG is able to corroborate the observed differing growth pathways, while also predicting that ELVOCs contribute more to growth than organic salt formation. However, most MABNAG model simulations tend to underpredict the observed growth rates between 10 and 20 nm in diameter; this underprediction may come from neglecting the contributions to growth from semi-to-low-volatility species or accretion reactions. Our results suggest that in addition to sulfuric acid, ELVOCs are also very important for growth in this rural setting. We discuss the limitations of our study that arise from not accounting for semi- and low-volatility organics, as well as nitrogen-containing species beyond ammonia and amines in the model. Quantitatively understanding the overall budget, evolution, and thermodynamic properties of lower-volatility organics in the atmosphere will be essential for improving global aerosol models.

Biomass-burning aerosols have a significant effect on global and regional aerosol climate forcings. To model the magnitude of these effects accurately requires knowledge of the size distribution of the emitted and evolving aerosol particles. Current biomass-burning inventories do not include size distributions, and global and regional models generally assume a fixed size distribution from all biomass-burning emissions. However, biomass-burning size distributions evolve in the plume due to coagulation and net organic aerosol (OA) evaporation or formation, and the plume processes occur on spacial scales smaller than global/regional-model grid boxes. The extent of this size-distribution evolution is dependent on a variety of factors relating to the emission source and atmospheric conditions. Therefore, accurately accounting for biomass-burning aerosol size in global models requires an effective aerosol size distribution that accounts for this sub-grid evolution and can be derived from available emission-inventory and meteorological parameters. In this paper, we perform a detailed investigation of the effects of coagulation on the aerosol size distribution in biomass-burning plumes. We compare the effect of coagulation to that of OA evaporation and formation. We develop coagulation-only parameterizations for effective biomass-burning size distributions using the SAM-TOMAS large-eddy simulation plume model. For the most-sophisticated parameterization, we use the Gaussian Emulation Machine for Sensitivity Analysis (GEM-SA) to build a parameterization of the aged size distribution based on the SAM-TOMAS output and seven inputs: emission median dry diameter, emission distribution modal width, mass emissions flux, fire area, mean boundary-layer wind speed, plume mixing depth, and time/distance since emission. This parameterization was tested against an independent set of SAM-TOMAS simulations and yields R2 values of 0.83 and 0.89 for Dpm and modal width, respectively. The size distribution is particularly sensitive to the mass emissions flux, fire area, wind speed, and time, and we provide simplified fits of the aged size distribution to just these input variables. The simplified fits were tested against 11 aged biomass-burning size distributions observed at the Mt. Bachelor Observatory in August 2015. The simple fits captured over half of the variability in observed Dpm and modal width even though the freshly emitted Dpm and modal widths were unknown. These fits may be used in global and regional aerosol models. Finally, we show that coagulation generally leads to greater changes in the particle size distribution than OA evaporation/formation does, using estimates of OA production/loss from the literature.

Open, uncontrolled combustion of domestic waste is a potentially significant source of aerosol; however, this aerosol source is not generally included in many global emissions inventories. To provide a first estimate of the aerosol radiative impacts from domestic-waste combustion, we incorporate the Wiedinmyer et al. (2014) emissions inventory into GEOS-Chem-TOMAS, a global chemical-transport model with online aerosol microphysics. We find domestic-waste combustion increases global-mean black carbon and organic aerosol concentrations by 8 and 6 %, respectively, and by greater than 40 % in some regions. Due to uncertainties regarding aerosol optical properties, we estimate the globally averaged aerosol direct radiative effect to range from −5 to −20 mW m−2; however, this range increases from −40 to +4 mW m−2 when we consider uncertainties in emission mass and size distribution. In some regions with significant waste combustion, such as India and China, the aerosol direct radiative effect may exceed −0.4 W m−2. Similarly, we estimate a cloud-albedo aerosol indirect effect of −13 mW m−2, with a range of −4 to −49 mW m−2 due to emission uncertainties. In the regions with significant waste combustion, the cloud-albedo aerosol indirect effect may exceed −0.4 W m−2.

Aerosols have important impacts on air quality and climate, but the processes affecting their removal from the atmosphere are not fully understood and are poorly constrained by observations. This makes modelled aerosol lifetimes uncertain. In this study, we make use of an observational constraint on aerosol lifetimes provided by radionuclide measurements and investigate the causes of differences within a set of global models. During the Fukushima Dai-Ichi nuclear power plant accident of March 2011, the radioactive isotopes cesium-137 (137Cs) and xenon-133 (133Xe) were released in large quantities. Cesium attached to particles in the ambient air, approximately according to their available aerosol surface area. 137Cs size distribution measurements taken close to the power plant suggested that accumulation-mode (AM) sulfate aerosols were the main carriers of cesium. Hence, 137Cs can be used as a proxy tracer for the AM sulfate aerosol's fate in the atmosphere. In contrast, the noble gas 133Xe behaves almost like a passive transport tracer. Global surface measurements of the two radioactive isotopes taken over several months after the release allow the derivation of a lifetime of the carrier aerosol. We compare this to the lifetimes simulated by 19 different atmospheric transport models initialized with identical emissions of 137Cs that were assigned to an aerosol tracer with each model's default properties of AM sulfate, and 133Xe emissions that were assigned to a passive tracer. We investigate to what extent the modelled sulfate tracer can reproduce the measurements, especially with respect to the observed loss of aerosol mass with time. Modelled 137Cs and 133Xe concentrations sampled at the same location and times as station measurements allow a direct comparison between measured and modelled aerosol lifetime. The e-folding lifetime τe, calculated from station measurement data taken between 2 and 9 weeks after the start of the emissions, is 14.3 days (95 % confidence interval 13.1–15.7 days). The equivalent modelled τe lifetimes have a large spread, varying between 4.8 and 26.7 days with a model median of 9.4 ± 2.3 days, indicating too fast a removal in most models. Because sufficient measurement data were only available from about 2 weeks after the release, the estimated lifetimes apply to aerosols that have undergone long-range transport, i.e. not for freshly emitted aerosol. However, modelled instantaneous lifetimes show that the initial removal in the first 2 weeks was quicker (lifetimes between 1 and 5 days) due to the emissions occurring at low altitudes and co-location of the fresh plume with strong precipitation. Deviations between measured and modelled aerosol lifetimes are largest for the northernmost stations and at later time periods, suggesting that models do not transport enough of the aerosol towards the Arctic. The models underestimate passive tracer (133Xe) concentrations in the Arctic as well but to a smaller extent than for the aerosol (137Cs) tracer. This indicates that in addition to too fast an aerosol removal in the models, errors in simulated atmospheric transport towards the Arctic in most models also contribute to the underestimation of the Arctic aerosol concentrations.

Measurements at high-Arctic sites (Alert, Nunavut, and Mt. Zeppelin, Svalbard) during the years 2011 to 2013 show a strong and similar annual cycle in aerosol number and size distributions. Each year at both sites, the number of aerosols with diameters larger than 20 nm exhibits a minimum in October and two maxima, one in spring associated with a dominant accumulation mode (particles 100 to 500 nm in diameter) and a second in summer associated with a dominant Aitken mode (particles 20 to 100 nm in diameter). Seasonal-mean aerosol effective diameter from measurements ranges from about 180 in summer to 260 nm in winter. This study interprets these annual cycles with the GEOS-Chem-TOMAS global aerosol microphysics model. Important roles are documented for several processes (new-particle formation, coagulation scavenging in clouds, scavenging by precipitation, and transport) in controlling the annual cycle in Arctic aerosol number and size. Our simulations suggest that coagulation scavenging of interstitial aerosols in clouds by aerosols that have activated to form cloud droplets strongly limits the total number of particles with diameters less than 200 nm throughout the year. We find that the minimum in total particle number in October can be explained by diminishing new-particle formation within the Arctic, limited transport of pollution from lower latitudes, and efficient wet removal. Our simulations indicate that the summertime-dominant Aitken mode is associated with efficient wet removal of accumulation-mode aerosols, which limits the condensation sink for condensable vapours. This in turn promotes new-particle formation and growth. The dominant accumulation mode during spring is associated with build up of transported pollution from outside the Arctic coupled with less-efficient wet-removal processes at colder temperatures. We recommend further attention to the key processes of new-particle formation, interstitial coagulation, and wet removal and their delicate interactions and balance in size-resolved aerosol simulations of the Arctic to reduce uncertainties in estimates of aerosol radiative effects on the Arctic climate.

Continuous hourly measurements of gas-phase ammonia (NH3(g)) were taken from 13 July to 7 August 2014 on a research cruise throughout Baffin Bay and the eastern Canadian Arctic Archipelago. Concentrations ranged from 30 to 650 ng m−3 (40–870 pptv) with the highest values recorded in Lancaster Sound (74°13′ N, 84°00′ W). Simultaneous measurements of total ammonium ([NHx]), pH and temperature in the ocean and in melt ponds were used to compute the compensation point (χ), which is the ambient NH3(g) concentration at which surface–air fluxes change direction. Ambient NH3(g) was usually several orders of magnitude larger than both χocean and χMP (3) indicating these surface pools are net sinks of NH3. Flux calculations estimate average net downward fluxes of 1.4 and 1.1 ng m−2 s−1 for the open ocean and melt ponds, respectively. Sufficient NH3(g) was present to neutralize non-sea-salt sulfate (nss-SO42−) in the boundary layer during most of the study. This finding was corroborated with a historical data set of PM2.5 composition from Alert, Nunavut (82°30′ N, 62°20′ W) wherein the median ratio of NH4+/nss-SO42− equivalents was greater than 0.75 in June, July and August. The GEOS-Chem chemical transport model was employed to examine the impact of NH3(g) emissions from seabird guano on boundary-layer composition and nss-SO42− neutralization. A GEOS-Chem simulation without seabird emissions underestimated boundary layer NH3(g) by several orders of magnitude and yielded highly acidic aerosol. A simulation that included seabird NH3 emissions was in better agreement with observations for both NH3(g) concentrations and nss-SO42− neutralization. This is strong evidence that seabird colonies are significant sources of NH3 in the summertime Arctic, and are ubiquitous enough to impact atmospheric composition across the entire Baffin Bay region. Large wildfires in the Northwest Territories were likely an important source of NH3, but their influence was probably limited to the Central Canadian Arctic. Implications of seabird-derived N-deposition to terrestrial and aquatic ecosystems are also discussed.

The analysis of aircraft-based measurements of clouds is critical for studies of aerosol and of clouds. Many such measurements have been taken, but it is difficult to compare such data across instruments, flights and campaigns. We present a new open-source software program, SAMAC (Software for Airborne Measurements of Aerosol and Clouds), that may enable a more systematic and comparable approach to the analysis of aerosol–cloud–precipitation data. The software offers a cooperative and reproducible approach to the analysis of aircraft measurements of clouds across campaigns. SAMAC is an object-oriented software program in which a cloud is an object; all the data related to a cloud is contained in the cloud object. The cloud objects come with built-in methods and functions that allow for the quick generation of basic plots and calculations, SAMAC provides a quick view of the data set and may be used to compare clouds and to filter for specific characteristics. Other researchers can readily use already submitted algorithms once their data is placed in the cloud structure provided, and they can contribute their own algorithms to the software for others to see and use. This approach would improve comparability, reproducibility and transparency by allowing others to replicate results and test the same algorithms on different data. SAMAC can be downloaded at https://github.com/StephGagne/SAMAC/releases.

Remote and free-tropospheric aerosols represent a large fraction of the climatic influence of aerosols; however, aerosol in these regions is less characterized than those polluted boundary layers. We evaluate aerosol size distributions predicted by the GEOS-Chem-TOMAS global chemical transport model with online aerosol microphysics using measurements from the peak of Whistler Mountain, British Columbia, Canada (2182 m a.s.l., hereafter referred to as Whistler Peak). We evaluate the model for predictions of aerosol number, size, and composition during periods of free-tropospheric (FT) and boundary-layer (BL) influence at "coarse" 4° × 5° and "nested" 0.5° × 0.667° resolutions by developing simple FT/BL filtering techniques. We find that using temperature as a proxy for upslope flow (BL influence) improved the model–measurement comparisons. The best threshold temperature was around 2 °C for the coarse simulations and around 6 °C for the nested simulations, with temperatures warmer than the threshold indicating boundary-layer air. Additionally, the site was increasingly likely to be in cloud when the measured relative humidity (RH) was above 90 %, so we do not compare the modeled and measured size distributions during these periods. With the inclusion of these temperature and RH filtering techniques, the model–measurement comparisons improved significantly. The slope of the regression for N80 (the total number of particles with particle diameter, Dp, > 80 nm) in the nested simulations increased from 0.09 to 0.65, R2 increased from 0.04 to 0.46, and log-mean bias improved from 0.95 to 0.07. We also perform simulations at the nested resolution without Asian anthropogenic emissions and without biomass-burning emissions to quantify the contribution of these sources to aerosols at Whistler Peak (through comparison with simulations with these emissions on). The long-range transport of Asian anthropogenic aerosol was found to be significant throughout all particle number concentrations, and increased N80 by more than 50 %, while decreasing the number of smaller particles because of suppression of new-particle formation and enhanced coagulation sink. Similarly, biomass burning influenced Whistler Peak during summer months, with an increase in N80 exceeding 5000 cm−3. Occasionally, Whistler Peak experienced N80 > 1000 cm−3 without significant influence from Asian anthropogenic or biomass-burning aerosol. Air masses were advected at low elevations through forested valleys during times when temperature and downwelling insolation were high, ideal conditions for formation of large sources of low-volatility biogenic secondary organic aerosol (SOA). This condensable material increased particle growth and hence N80. The low-cost filtering techniques and source apportionment used in this study can be used in other global models to give insight into the sources and processes that shape the aerosol at mountain sites, leading to a better understanding of mountain meteorology and chemistry.

Aerosol observations above the Southern Ocean and Antarctic sea ice are scarce. Measurements of aerosols and atmospheric composition were made in East Antarctic pack ice on board the Australian icebreaker Aurora Australis during the spring of 2012. One particle formation event was observed during the 32 days of observations. This event occurred on the only day to exhibit extended periods of global irradiance in excess of 600 W m−2. Within the single air mass influencing the measurements, number concentrations of particles larger than 3 nm (CN3) reached almost 7700 cm−3 within a few hours of clouds clearing, and grew at rates of 5.6 nm h−1. Formation rates of 3 nm particles were in the range of those measured at other Antarctic locations at 0.2–1.1 ± 0.1 cm−3 s−1. Our investigations into the nucleation chemistry found that there were insufficient precursor concentrations for known halogen or organic chemistry to explain the nucleation event. Modelling studies utilising known sulfuric acid nucleation schemes could not simultaneously reproduce both particle formation or growth rates. Surprising correlations with total gaseous mercury (TGM) were found that, together with other data, suggest a mercury-driven photochemical nucleation mechanism may be responsible for aerosol nucleation. Given the very low vapour pressures of the mercury species involved, this nucleation chemistry is likely only possible where pre-existing aerosol concentrations are low and both TGM concentrations and solar radiation levels are relatively high (∼ 1.5 ng m−3 and &geq; 600 W m−2, respectively), such as those observed in the Antarctic sea ice boundary layer in this study or in the global free troposphere, particularly in the Northern Hemisphere.

The oxidation of biogenic volatile organic compounds (BVOCs) gives a range of products, from semi-volatile to extremely low-volatility compounds. To treat the interaction of these secondary organic vapours with the particle phase, global aerosol microphysics models generally use either a thermodynamic partitioning approach (assuming instant equilibrium between semi-volatile oxidation products and the particle phase) or a kinetic approach (accounting for the size dependence of condensation). We show that model treatment of the partitioning of biogenic organic vapours into the particle phase, and consequent distribution of material across the size distribution, controls the magnitude of the first aerosol indirect effect (AIE) due to biogenic secondary organic aerosol (SOA). With a kinetic partitioning approach, SOA is distributed according to the existing condensation sink, enhancing the growth of the smallest particles, i.e. those in the nucleation mode. This process tends to increase cloud droplet number concentrations in the presence of biogenic SOA. By contrast, an approach that distributes SOA according to pre-existing organic mass restricts the growth of the smallest particles, limiting the number that are able to form cloud droplets. With an organically mediated new particle formation mechanism, applying a mass-based rather than a kinetic approach to partitioning reduces our calculated global mean AIE due to biogenic SOA by 24 %. Our results suggest that the mechanisms driving organic partitioning need to be fully understood in order to accurately describe the climatic effects of SOA.

Smog chambers are extensively used to study processes that drive gas and particle evolution in the atmosphere. A limitation of these experiments is that particles and gas-phase species may be lost to chamber walls on shorter timescales than the timescales of the atmospheric processes being studied in the chamber experiments. These particle and vapor wall losses have been investigated in recent studies of secondary organic aerosol (SOA) formation, but they have not been systematically investigated in experiments of primary emissions from combustion. The semi-volatile nature of combustion emissions (e.g. from wood smoke) may complicate the behavior of particle and vapor wall deposition in the chamber over the course of the experiments due to the competition between gas/particle and gas/wall partitioning. Losses of vapors to the walls may impact particle evaporation in these experiments, and potential precursors for SOA formation from combustion may be lost to the walls, causing underestimations of aerosol yields. Here, we conduct simulations to determine how particle and gas-phase wall losses contributed to the observed evolution of the aerosol during experiments in the third Fire Lab At Missoula Experiment (FLAME III). We use the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithm coupled with the organic volatility basis set (VBS) and wall-loss formulations to examine the predicted extent of particle and vapor wall losses. We limit the scope of our study to the dark periods in the chamber before photo-oxidation to simplify the aerosol system for this initial study. Our model simulations suggest that over one-third of the initial particle-phase organic mass (41 %) was lost during the experiments, and over half of this particle-organic mass loss was from direct particle wall loss (65 % of the loss) with the remainder from evaporation of the particles driven by vapor losses to the walls (35 % of the loss). We perform a series of sensitivity tests to understand uncertainties in our simulations. Uncertainty in the initial wood-smoke volatility distribution contributes 18 % uncertainty to the final particle-organic mass remaining in the chamber (relative to base-assumption simulation). We show that the total mass loss may depend on the effective saturation concentration of vapor with respect to the walls as these values currently vary widely in the literature. The details of smoke dilution during the filling of smog chambers may influence the mass loss to the walls, and a dilution of ~ 25:1 during the experiments increased particle-organic mass loss by 33 % compared to a simulation where we assume the particles and vapors are initially in equilibrium in the chamber. Finally, we discuss how our findings may influence interpretations of emission factors and SOA production in wood-smoke smog-chamber experiments.

Aerosol emissions from biofuel combustion impact both health and climate; however, while reducing emissions through improvements to combustion technologies will improve health, the net effect on climate is largely unconstrained. In this study, we examine sensitivities in global aerosol concentration, direct radiative climate effect, and cloud-albedo aerosol indirect climate effect to uncertainties in biofuel emission factors, optical mixing state, and model nucleation and background secondary organic aerosol (SOA). We use the Goddard Earth Observing System global chemical-transport model (GEOS-Chem) with TwO Moment Aerosol Sectional (TOMAS) microphysics. The emission factors include amount, composition, size, and hygroscopicity, as well as optical mixing-state properties. We also evaluate emissions from domestic coal use, which is not biofuel but is also frequently emitted from homes. We estimate the direct radiative effect assuming different mixing states (homogeneous, core-shell, and external) with and without absorptive organic aerosol (brown carbon). We find the global-mean direct radiative effect of biofuel emissions ranges from −0.02 to +0.06 W m−2 across all simulation/mixing-state combinations with regional effects in source regions ranging from −0.2 to +0.8 W m−2. The global-mean cloud-albedo aerosol indirect effect (AIE) ranges from +0.01 to −0.02 W m−2 with regional effects in source regions ranging from −1.0 to −0.05 W m−2. The direct radiative effect is strongly dependent on uncertainties in emissions mass, composition, emissions aerosol size distributions, and assumed optical mixing state, while the indirect effect is dependent on the emissions mass, emissions aerosol size distribution, and the choice of model nucleation and secondary organic aerosol schemes. The sign and magnitude of these effects have a strong regional dependence. We conclude that the climate effects of biofuel aerosols are largely unconstrained, and the overall sign of the aerosol effects is unclear due to uncertainties in model inputs. This uncertainty limits our ability to introduce mitigation strategies aimed at reducing biofuel black carbon emissions in order to counter warming effects from greenhouse gases. To better understand the climate impact of particle emissions from biofuel combustion, we recommend field/laboratory measurements to narrow constraints on (1) emissions mass, (2) emission size distribution, (3) mixing state, and (4) ratio of black carbon to organic aerosol.

In this paper, we investigate the coagulation of interstitial aerosol particles (particles too small to activate to cloud droplets) with cloud drops, a process often ignored in aerosol-climate models. We use the GEOS-Chem-TOMAS (Goddard Earth Observing System-Chemistry TwO-Moment Aerosol Sectional) global chemical transport model with aerosol microphysics to calculate the changes in the aerosol size distribution, cloud-albedo aerosol indirect effect, and direct aerosol effect due to the interstitial coagulation process. We find that inclusion of interstitial coagulation in clouds lowers total particle number concentrations by 15–21% globally, where the range is due to varying assumptions regarding activation diameter, cloud droplet size, and ice cloud physics. The interstitial coagulation process lowers the concentration of particles with dry diameters larger than 80 nm (a proxy for larger CCN) by 10–12%. These 80 nm particles are not directly removed by the interstitial coagulation but are reduced in concentration because fewer smaller particles grow to diameters larger than 80 nm. The global aerosol indirect effect of adding interstitial coagulation varies from +0.4 to +1.3 W m−2 where again the range depends on our cloud assumptions. Thus, the aerosol indirect effect of this process is significant, but the magnitude depends greatly on assumptions regarding activation diameter, cloud droplet size, and ice cloud physics. The aerosol direct effect of the interstitial coagulation process is minor (< 0.01 W m−2) due to the shift in the aerosol size distribution at sizes where scattering is most effective being small. We recommend that this interstitial scavenging process be considered in aerosol models when the size distribution and aerosol indirect effects are important.

Emissions of biogenic volatile organic compounds (BVOCs) have changed in the past millennium due to changes in land use, temperature, and CO2 concentrations. Recent reconstructions of BVOC emissions have predicted that global isoprene emissions have decreased, while monoterpene and sesquiterpene emissions have increased; however, all three show regional variability due to competition between the various influencing factors. In this work, we use two modeled estimates of BVOC emissions from the years 1000 to 2000 to test the effect of anthropogenic changes to BVOC emissions on secondary organic aerosol (SOA) formation, global aerosol size distributions, and radiative effects using the GEOS-Chem-TOMAS (Goddard Earth Observing System; TwO-Moment Aerosol Sectional) global aerosol microphysics model. With anthropogenic emissions (e.g., SO2, NOx, primary aerosols) turned off and BVOC emissions changed from year 1000 to year 2000 values, decreases in the number concentration of particles of size Dp > 80 nm (N80) of > 25% in year 2000 relative to year 1000 were predicted in regions with extensive land-use changes since year 1000 which led to regional increases in the combined aerosol radiative effect (direct and indirect) of > 0.5 W m−2 in these regions. We test the sensitivity of our results to BVOC emissions inventory, SOA yields, and the presence of anthropogenic emissions; however, the qualitative response of the model to historic BVOC changes remains the same in all cases. Accounting for these uncertainties, we estimate millennial changes in BVOC emissions cause a global mean direct effect of between +0.022 and +0.163 W m−2 and the global mean cloud-albedo aerosol indirect effect of between −0.008 and −0.056 W m−2. This change in aerosols, and the associated radiative forcing, could be a largely overlooked and important anthropogenic aerosol effect on regional climates.