ALBERT

Description: 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.

Description: Mounting evidence from field and laboratory observations coupled with atmospheric model analyses shows that primary combustion emissions of organic compounds dynamically partition between the vapor and particulate phases, especially as near-source emissions dilute and cool to ambient conditions. The most recent version of the Community Multiscale Air Quality model version 5.2 (CMAQv5.2) accounts for the semivolatile partitioning and gas-phase aging of these primary organic aerosol (POA) compounds consistent with experimentally derived parameterizations. We also include a new surrogate species, potential secondary organic aerosol from combustion emissions (pcSOA), which provides a representation of the secondary organic aerosol (SOA) from anthropogenic combustion sources that could be missing from current chemical transport model predictions. The reasons for this missing mass likely include the following: (1) unspeciated semivolatile and intermediate volatility organic compound (SVOC and IVOC, respectively) emissions missing from current inventories, (2) multigenerational aging of organic vapor products from known SOA precursors (e.g., toluene, alkanes), (3) underestimation of SOA yields due to vapor wall losses in smog chamber experiments, and (4) reversible organic compounds–water interactions and/or aqueous-phase processing of known organic vapor emissions. CMAQ predicts the spatially averaged contribution of pcSOA to OA surface concentrations in the continental United States to be 38.6 and 23.6 % in the 2011 winter and summer, respectively. Whereas many past modeling studies focused on a particular measurement campaign, season, location, or model configuration, we endeavor to evaluate the model and important uncertain parameters with a comprehensive set of United States-based model runs using multiple horizontal scales (4 and 12 km), gas-phase chemical mechanisms, and seasons and years. The model with representation of semivolatile POA improves predictions of hourly OA observations over the traditional nonvolatile model at sites during field campaigns in southern California (CalNex, May–June 2010), northern California (CARES, June 2010), the southeast US (SOAS, June 2013; SEARCH, January and July, 2011). Model improvements manifest better correlations (e.g., the correlation coefficient at Pasadena at night increases from 0.38 to 0.62) and reductions in underprediction during the photochemically active afternoon period (e.g., bias at Pasadena from −5.62 to −2.42 µg m−3). Daily averaged predictions of observations at routine-monitoring networks from simulations over the continental US (CONUS) in 2011 show modest improvement during winter, with mean biases reducing from 1.14 to 0.73 µg m−3, but less change in the summer when the decreases from POA evaporation were similar to the magnitude of added SOA mass. Because the model-performance improvement realized by including the relatively simple pcSOA approach is similar to that of more-complicated parameterizations of OA formation and aging, we recommend caution when applying these more-complicated approaches as they currently rely on numerous uncertain parameters. The pcSOA parameters optimized for performance at the southern and northern California sites lead to higher OA formation than is observed in the CONUS evaluation. This may be due to any of the following: variations in real pcSOA in different regions or time periods, too-high concentrations of other OA sources in the model that are important over the larger domain, or other model issues such as loss processes. This discrepancy is likely regionally and temporally dependent and driven by interferences from factors like varying emissions and chemical regimes.

Description: pH is a fundamental aerosol property that affects ambient particle concentration and composition, linking pH to all aerosol environmental impacts. Here, PM1 and PM2. 5 pH are calculated based on data from measurements during the California Research at the Nexus of Air Quality and Climate Change (CalNex) study from 15 May to 15 June 2010 in Pasadena, CA. Particle pH and water were predicted with the ISORROPIA-II thermodynamic model and validated by comparing predicted to measured gas–particle partitioning of inorganic nitrate, ammonium, and chloride. The study mean ± standard deviation PM1 pH was 1.9 ± 0.5 for the SO42−–NO3−–NH4+–HNO3–NH3 system. For PM2. 5, internal mixing of sea salt components (SO42−–NO3−–NH4+–Na+–Cl−–K+–HNO3–NH3–HCl system) raised the bulk pH to 2.7 ± 0.3 and improved predicted nitric acid partitioning with PM2. 5 components. The results show little effect of sea salt on PM1 pH, but significant effects on PM2. 5 pH. A mean PM1 pH of 1.9 at Pasadena was approximately one unit higher than what we have reported in the southeastern US, despite similar temperature, relative humidity, and sulfate ranges, and is due to higher total nitrate concentrations (nitric acid plus nitrate) relative to sulfate, a situation where particle water is affected by semi-volatile nitrate concentrations. Under these conditions nitric acid partitioning can further promote nitrate formation by increasing aerosol water, which raises pH by dilution, further increasing nitric acid partitioning and resulting in a significant increase in fine particle nitrate and pH. This study provides insights into the complex interactions between particle pH and nitrate in a summertime coastal environment and a contrast to recently reported pH in the eastern US in summer and winter and the eastern Mediterranean. All studies have consistently found highly acidic PM1 with pH generally below 3.

Description: The occurrence of frequent aerosol nucleation and growth events in the Arctic during summertime may impact the region's climate through increasing the number of cloud condensation nuclei in the Arctic atmosphere. Measurements of aerosol size distributions and aerosol composition were taken during the summers of 2015 and 2016 at Eureka and Alert on Ellesmere Island in Nunavut, Canada. These results provide a better understanding of the frequency and spatial extent of elevated Aitken mode aerosol concentrations as well as of the composition and sources of aerosol mass during particle growth. Frequent appearances of small particles followed by growth occurred throughout the summer. These particle growth events were observed beginning in June with the melting of the sea ice rather than with the polar sunrise, which strongly suggests that influence from the marine boundary layer was the primary cause of the events. Correlated particle growth events at the two sites, separated by 480 km, indicate conditions existing over large scales play a key role in determining the timing and the characteristics of the events. In addition, aerosol mass spectrometry measurements were used to analyze the size-resolved chemical composition of aerosols during two selected growth events. It was found that particles with diameters between 50 and 80 nm (physical diameter) during these growth events were predominately organic with only a small sulfate contribution. The oxidation of the organics also changed with particle size, with the fraction of organic acids increasing with diameter from 80 to 400 nm. The growth events at Eureka were observed most often when the temperature inversion between the sea and the measurement site (at 610 m a.s.l.) was non-existent or weak, presumably creating conditions with low aerosol condensation sink and allowing fresh marine emissions to be mixed upward to the observatory's altitude. While the nature of the gaseous precursors responsible for the growth events is still poorly understood, oxidation of dimethyl sulfide alone to produce particle-phase sulfate or methanesulfonic acid was inconsistent with the measured aerosol composition, suggesting the importance of other gas-phase organic compounds condensing for particle growth.

Description: Secondary organic aerosol (SOA) is an important contributor to fine particulate matter (PM) mass in polluted regions, and its modeling remains poorly constrained. A box model is developed that uses recently published literature parameterizations and data sets to better constrain and evaluate the formation pathways and precursors of urban SOA during the CalNex 2010 campaign in Los Angeles. When using the measurements of intermediate-volatility organic compounds (IVOCs) reported in Zhao et al. (2014) and of semi-volatile organic compounds (SVOCs) reported in Worton et al. (2014) the model is biased high at longer photochemical ages, whereas at shorter photochemical ages it is biased low, if the yields for VOC oxidation are not updated. The parameterizations using an updated version of the yields, which takes into account the effect of gas-phase wall losses in environmental chambers, show model–measurement agreement at longer photochemical ages, even though some low bias at short photochemical ages still remains. Furthermore, the fossil and non-fossil carbon split of urban SOA simulated by the model is consistent with measurements at the Pasadena ground site. Multi-generation oxidation mechanisms are often employed in SOA models to increase the SOA yields derived from environmental chamber experiments in order to obtain better model–measurement agreement. However, there are many uncertainties associated with these aging mechanisms. Thus, SOA formation in the model is compared to data from an oxidation flow reactor (OFR) in order to constrain SOA formation at longer photochemical ages than observed in urban air. The model predicts similar SOA mass at short to moderate photochemical ages when the aging mechanisms or the updated version of the yields for VOC oxidation are implemented. The latter case has SOA formation rates that are more consistent with observations from the OFR though. Aging mechanisms may still play an important role in SOA chemistry, but the additional mass formed by functionalization reactions during aging would need to be offset by gas-phase fragmentation of SVOCs. All the model cases evaluated in this work show a large majority of the urban SOA (70–83 %) at Pasadena coming from the oxidation of primary SVOCs (P-SVOCs) and primary IVOCs (P-IVOCs). The importance of these two types of precursors is further supported by analyzing the percentage of SOA formed at long photochemical ages (1.5 days) as a function of the precursor rate constant. The P-SVOCs and P-IVOCs have rate constants that are similar to highly reactive VOCs that have been previously found to strongly correlate with SOA formation potential measured by the OFR. Finally, the volatility distribution of the total organic mass (gas and particle phase) in the model is compared against measurements. The total SVOC mass simulated is similar to the measurements, but there are important differences in the measured and modeled volatility distributions. A likely reason for the difference is the lack of particle-phase reactions in the model that can oligomerize and/or continue to oxidize organic compounds even after they partition to the particle phase.

Description: Community Multiscale Air Quality (CMAQ) model simulations utilizing the traditional organic aerosol (OA) treatment (CMAQ-AE6) and a volatility basis set (VBS) treatment for OA (CMAQ-VBS) were evaluated against measurements collected at routine monitoring networks (Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE)) and those collected during the 2010 California at the Nexus of Air Quality and Climate Change (CalNex) field campaign to examine important sources of OA in southern California. Traditionally, CMAQ treats primary organic aerosol (POA) as nonvolatile and uses a two-product framework to represent secondary organic aerosol (SOA) formation. CMAQ-VBS instead treats POA as semivolatile and lumps OA using volatility bins spaced an order of magnitude apart. The CMAQ-VBS approach underpredicted organic carbon (OC) at IMPROVE and CSN sites to a greater degree than CMAQ-AE6 due to the semivolatile POA treatment. However, comparisons to aerosol mass spectrometer (AMS) measurements collected at Pasadena, CA, indicated that CMAQ-VBS better represented the diurnal profile and primary/secondary split of OA. CMAQ-VBS SOA underpredicted the average measured AMS oxygenated organic aerosol (OOA, a surrogate for SOA) concentration by a factor of 5.2, representing a considerable improvement to CMAQ-AE6 SOA predictions (factor of 24 lower than AMS). We use two new methods, one based on species ratios (SOA/ΔCO and SOA/Ox) and another on a simplified SOA parameterization, to apportion the SOA underprediction for CMAQ-VBS to slow photochemical oxidation (estimated as 1.5 ×  lower than observed at Pasadena using −log(NOx : NOy)), low intrinsic SOA formation efficiency (low by 1.6 to 2 ×  for Pasadena), and low emissions or excessive dispersion for the Pasadena site (estimated to be 1.6 to 2.3 ×  too low/excessive). The first and third factors are common to CMAQ-AE6, while the intrinsic SOA formation efficiency for that model is estimated to be too low by about 7 × . From source-apportioned model results, we found most of the CMAQ-VBS modeled POA at the Pasadena CalNex site was attributable to meat cooking emissions (48 %, consistent with a substantial fraction of cooking OA in the observations). This is compared to 18 % from gasoline vehicle emissions, 13 % from biomass burning (in the form of residential wood combustion), and 8 % from diesel vehicle emissions. All "other" inventoried emission sources (e.g., industrial, point, and area sources) comprised the final 13 %. The CMAQ-VBS semivolatile POA treatment underpredicted AMS hydrocarbon-like OA (HOA) + cooking-influenced OA (CIOA) at Pasadena by a factor of 1.8 compared to a factor of 1.4 overprediction of POA in CMAQ-AE6, but it did capture the AMS diurnal profile of HOA and CIOA well, with the exception of the midday peak. Overall, the CMAQ-VBS with its semivolatile treatment of POA, SOA from intermediate volatility organic compounds (IVOCs), and aging of SOA improves SOA model performance (though SOA formation efficiency is still 1.6–2 ×  too low). However, continued efforts are needed to better understand assumptions in the parameterization (e.g., SOA aging) and provide additional certainty to how best to apply existing emission inventories in a framework that treats POA as semivolatile, which currently degrades existing model performance at routine monitoring networks. The VBS and other approaches (e.g., AE6) require additional work to appropriately incorporate IVOC emissions and subsequent SOA formation.

Description: Mounting evidence from field and laboratory observations coupled with atmospheric model analyses show that primary combustion emissions of organic compounds dynamically partition between the vapor and particulate phases, especially as near-source emissions dilute and cool to ambient conditions. The most recent version of the Community Multiscale Air Quality (CMAQ) Model v5.2 accounts for the semivolatile partitioning and gas-phase aging of these primary organic aerosol (POA) compounds consistent with experimentally derived parameterizations. We also include a new surrogate species, potential secondary organic aerosol from combustion emissions (pcSOA), which provides a representation of the SOA from anthropogenic combustion sources that could be missing from current chemical transport model predictions. The reasons for this missing mass likely include the following: 1) unspeciated semivolatile and intermediate volatility organic compound (SVOC and IVOC, respectively) emissions missing from current inventories, 2) multigenerational aging of organic vapor products from known SOA precursors (e.g. toluene, alkanes, etc), 3) underestimation of SOA yields due to vapor wall losses in smog chamber experiments, and 4) reversible organic-water interactions and/or aqueous-phase processing of known organic vapor emissions. CMAQ predicts the spatially-averaged contribution of pcSOA to OA surface concentrations in the continental United States to be 38.6 % and 23.6 % in the 2011 winter and summer, respectively. Whereas many past modeling studies focused on a particular measurement campaign, season, location, or model configuration, we endeavor to evaluate the model and important uncertain parameters with a comprehensive set of United States-based model runs using multiple horizontal scales (4 km and 12 km), gas-phase chemical mechanisms, seasons and years. The model with representation of semivolatile POA improves predictions of hourly OA observations over the traditional nonvolatile model at sites during field campaigns in southern California (CalNex, May–June 2010), northern California (CARES, June 2010), the southeast US (SOAS, June 2013; SEARCH, January and July, 2011). Model improvements manifest better correlations (e.g. correlation coefficient at Pasadena at night increases from 0.38 to 0.62) and reductions in underprediction during the photochemically active afternoon period (e.g. bias at Pasadena from −5.62 to −2.42 μg m−3). Daily-averaged predictions of observations at routine monitoring networks from simulations over the continental U.S. (CONUS) in 2011 show modest improvement during winter with mean biases reducing from 1.14 to 0.73 μg m−3, but less change in the summer when the decreases from POA evaporation were similar to the magnitude of added SOA mass. Because the model-performance improvement realized by including the relatively simple pcSOA approach is similar to that of more-complicated parameterizations of OA formation and aging, we recommend caution when applying these more-complicated approaches as they currently rely on numerous uncertain parameters. The pcSOA parameters optimized for performance at the southern and northern California sites lead to higher OA formation than is observed in the CONUS evaluation. This may be due to any of the following: variations in real pcSOA in different regions or time periods, too high concentrations of other OA sources in the model that are important over the larger domain, or other model issues such as loss processes. This discrepancy is likely regionally and temporally dependent and driven by interferences from factors like varying emissions and chemical regimes.

Description: The occurrence of frequent aerosol nucleation and growth events in the Arctic during summertime may impact the region’s climate through increasing the number of cloud condensation nuclei in the Arctic atmosphere. Measurements of aerosol size distributions and aerosol composition were taken during the summers of 2015 and 2016 at Eureka and Alert on Ellesmere Island in Nunavut, Canada. The corresponding results provide a better understanding of the frequency and spatial extent of these nucleation and growth events as well as of the composition and sources of aerosol mass during particle growth. These events are observed beginning in June with the melting of the sea ice rather than with polar sunrise, which strongly suggests emissions from marine sources are the primary cause of the events. Frequent particle nucleation followed by growth occurs throughout the summer. Correlated particle growths events at the two sites, separated by 480km, indicate conditions existing over such large scales play a key role in determining the timing and the characteristics of the events. In addition, aerosol mass spectrometry measurements are used to analyze the size-resolved chemical composition of aerosols during two selected growth events. It is found that particles with diameters smaller than 100nm are predominately organic with only a small sulphate contribution. The oxidation of the organic fraction also changes with particle size with larger particles containing a greater fraction of organic acids relative to other non-acid oxygenates (e.g. alcohols or aldehydes). It is also observed that the relative amount of m/z 44 in the measured mass spectra increases during the growth events suggesting increases in organic acid concentrations in the particle phase. The nucleation and growth events at Eureka are observed most often when the temperature inversion between the sea and the measurement site (at 610ma.s.l.) is non-existent or weak allowing presumably fresh marine emissions to be mixed upward to the observatory altitude. While the nature of the gaseous precursors responsible for the growth events are poorly understood, oxidation of dimethyl sulphide alone to produce particle phase sulphate or methanesulphonic acid is not consistent with the measured aerosol composition, suggesting the importance of condensation of other gas phase organic compounds for particle growth.

Description: Secondary Organic Aerosols (SOA) are important contributors to fine PM mass in polluted regions, and their modeling remains poorly constrained. A box model is developed that uses recently published literature parameterizations and data sets to better constrain and evaluate the formation pathways and precursors of urban SOA during the CalNex 2010 campaign in Los Angeles. When using the measurements of IVOCs reported in Zhao et al. (2014) and of SVOCs reported in Worton et al. (2014) the model is biased high at longer photochemical ages whereas at shorter photochemical ages it is biased low, if the yields for VOC oxidation are not updated. The parameterizations using an updated version of the yields, which takes into account the effect of gas phase wall-losses in environmental chambers, show model/measurement agreement at longer photochemical ages, even though some low bias at short photochemical ages still remains. Furthermore, the fossil/non-fossil carbon split of urban SOA simulated by the model is consistent with measurements at the Pasadena ground site. Multi-generation oxidation mechanisms are often employed in SOA models to increase the SOA yields derived from environmental chamber experiments in order to obtain better model/measurement agreement. However, there are many uncertainties associated with these "aging" mechanisms. Thus, SOA formation in the model is compared against data from an oxidation flow reactor (OFR) in order to constrain SOA formation at longer photochemical ages than observed in urban air. The model predicts similar SOA mass when the "aging" mechanisms or the updated version of the yields for VOC oxidation are implemented. The latter case though has SOA formation rates that are more consistent with observations from the OFR. All the model cases evaluated in this work have a large majority of the urban SOA (70–86 %) at Pasadena coming from the oxidation of P-SVOCs and P-IVOCs. The importance of these two types of precursors is further supported by analyzing the percentage of SOA formed at long photochemical ages (1.5 days) as a function of the precursor rate constant. The P-SVOCs and P-IVOCs have rate constants that are similar to highly reactive VOCs that have been previously found to strongly correlate with SOA formation potential measured by the OFR. Finally, the volatility distribution of the total organic mass (gas and particle phase) in the model is compared against measurements. The total SVOC mass simulated is similar to the measurements, but there are important differences in the measured and modeled volatility distributions. A likely reason for the difference is the lack of particle-phase reactions in the model that can oligomerize and/or continue to oxidize organic compounds even after they partition to the particle phase.

Description: pH is a fundamental aerosol property that affects ambient particle concentration and composition, linking pH to all aerosol environmental impacts. Here, PM1 and PM2.5 pH are calculated based on data from measurements during the California Research at the Nexus of Air Quality and Climate Change (CalNex) study from 15 May to 15 June 2010 in Pasadena CA. Particle pH and water were predicted with the ISORROPIA-II thermodynamic model and validated by comparing predicted to measured gas-particle partitioning of inorganic nitrate, ammonium and chloride. The study mean ± standard deviation PM1 pH was 1.9 ± 0.5 for the SO42−-NO3−-NH4+-HNO3-NH3 system. For PM2.5, internal mixing of sea salt components (SO42−-NO3−-NH4+-Na+-Cl−-K+-HNO3-NH3-HCl system) raised the bulk pH to 2.7 ± 0.3 and improved predicted nitric acid partitioning with PM2.5 components. The results show little effect of sea salt on PM1 pH, but significant effects on PM2.5 pH. A mean PM1 pH of 1.9 at Pasadena was approximately one unit higher than what we have reported in the southeastern US, despite similar temperature, relative humidity and sulfate ranges and is due to higher total nitrate concentrations (nitric acid plus nitrate) relative to sulfate, a situation where particle water is affected by semi-volatile nitrate concentrations. Under these conditions nitric acid partitioning can further promote nitrate formation by increasing aerosol water, which raises pH by dilution, further increasing nitric acid partitioning and resulting in a significant increase in fine particle nitrate and pH. This study provides insights on the complex interactions between particle pH and nitrate in a summertime coastal environment and a contrast to recently reported pH in the eastern US in summer and winter and the eastern Mediterranean. All studies have consistently found highly acidic PM1 with pH generally below 3.