Search

Passive satellite observations play an important role in monitoring global aerosol properties and helping quantify aerosol radiative forcing in the climate system. The quality of aerosol retrievals from the satellite platform relies on well-calibrated radiance measurements from multiple spectral bands, and the availability of appropriate particle optical models. Inaccurate scattering phase function assumptions can introduce large retrieval errors. The high-spatial resolution, dual-view observations from the advanced baseline imagers onboard the two most recent geostationary operational environmental satellites (GOES), East and West, provide a unique opportunity to better constrain the aerosol phase function. Using dual GOES reflectance measurements for a dust event in the Gulf of Mexico in 2019, we demonstrate how a first-guess phase function can be reconstructed by considering the variations in observed scattering angles throughout the day. Using the reconstructed phase function, aerosol optical depth retrievals from the two satellites are self-consistent and agree well with surface-based optical depth estimates. We evaluate our methodology and reconstructed phase function against independent retrievals made from low-Earth-orbit multi-angle observations for a different dust event in 2020. Our new aerosol optical depth retrievals have a root-mean-square-difference of 0.019–0.047. Furthermore, the retrievals between the two geostationary satellites for this case agree within about 0.059 ± 0.072, as compared to larger discrepancies between the operational GOES products at times, which do not employ the dual-view technique.

Lofted mineral dust over data-sparse regions presents considerable challenges to satellite-based remote sensing methods and numerical weather prediction alike. The Southwest Asia domain is replete with such examples, with its diverse array of dust sources, dust mineralogy, and meteorologically-driven lofting mechanisms on multiple spatial and temporal scales. A microcosm of these challenges occurred over 3–4 August 2016 when two dust plumes, one lofted within an inland dry air mass and another embedded within a moist air mass, met over the Southern Arabian Peninsula. Whereas conventional infrared-based techniques readily detected the dry air mass dust plume, they experienced marked difficulties in detecting the moist air mass dust plume, which only became apparent when visible reflectance revealed it crossing over an adjacent dark water background. In combining information from numerical modelling, multi-satellite/multi-sensor observations of lofted dust and moisture profiles, and idealized radiative transfer simulations, we develop a better understanding of the environmental controls of this event, characterizing the sensitivity of infrared-based dust detection to column water vapor, dust vertical extent, and dust optical properties. Differences in assumptions of dust complex refractive index translate to variations in the sign and magnitude of the split-window brightness temperature difference commonly used for detecting mineral dust. A multi-sensor technique for mitigating the radiative masking effects of water vapor via modulation of the split-window dust-detection threshold, predicated on idealized simulations tied to these driving factors, is proposed and demonstrated. The new technique, indexed to independent-sensor description of the surface-to-500 mb atmospheric column moisture, reveals parts of the missing dust plume embedded in the moist air mass, with best performance over land surfaces.

This high-resolution numerical modeling study investigates the potential range of impact of surface-lofted dust aerosols on the mean radiative fluxes and temperature changes associated with a dust-lofting episode over the Arabian Peninsula (2–5 August 2016). Assessing the potential for lofted dust to impact the radiation budget and temperature response in regions of the world that are prone to intense dust storms is important due to the impact of such temperature perturbations on thermally driven mesoscale circulations such as sea breezes and convective outflows. As such, sensitivity simulations using various specifications of the dust-erodible fraction were performed using two high-resolution mesoscale models that use similar dust-lofting physics based on threshold friction wind velocity and soil characteristics. The dust-erodible fraction, which represents the fraction (0.0 to 1.0) of surface soil that could be mechanically lifted by the wind and controls the location and magnitude of surface dust flux, was varied for three experiments with each model. The “Idealized” experiments, which used an erodible fraction of 1.0 over all land grid cells, represent the upper limit on dust lofting within each modeling framework, the “Ginoux” experiments used a 1∘ resolution, spatially varying erodible fraction dataset based on topographic depressions, and the “Walker” experiments used satellite-identified, 1 km resolution data with known lofting locations given an erodible fraction of 1.0. These simulations were compared with a “No-Dust” experiment in which no dust aerosols were permitted. The use of erodible fraction databases in the Ginoux and Walker simulations produced similar dust loading which was more realistic than that produced in the Idealized lofting simulations. Idealized lofting in this case study generated unrealistically large amounts of dust compared with observations of aerosol optical depth (AOD) due to the lack of locational constraints. Generally, the simulations with enhanced dust mass via surface lofting experienced reductions in daytime insolation due to aerosol scattering effects as well as reductions in nighttime radiative cooling due to aerosol absorption effects. These radiative responses were magnified with increasing amounts of dust loading. In the Idealized simulation with extreme (AOD > 5) dust amounts, these radiative responses suppressed the diurnal temperature range. In the Ginoux and Walker simulations with moderate (AOD ∼1–3) amounts of lofted dust, the presence of dust still strongly impacted the radiative fluxes but only marginally modified the low-level temperature. The dust-induced near-surface temperature change was limited due to competing thermal responses to changes in the net radiative fluxes and the dust-layer radiative heating rates. Compared to the Ginoux simulation, the use of increased resolution in dust-erodible fraction inventories in the Walker simulations led to enhanced fine-scale horizontal variability in lofted dust and a modest increase in the mean dust concentration profile and radiative or thermal responses. This study discusses the utility of using high-resolution dust source databases for simulating lofted dust, the need for greater spatial coverage of in situ aerosol observations in dust-prone regions, the impacts of dust on the local radiation budget and surface thermal conditions, and the potential dust radiative impacts on thermally driven mesoscale features.

Here, we present a multi-season study of ice-nucleating particles (INPs) active via the immersion freezing mechanism, which took place in north-central Argentina, a worldwide hotspot for mesoscale convective storms. INPs were measured untreated, after heating to 95°C, and after hydrogen peroxide digestion. No seasonal cycle of INP concentrations was observed. Heat labile INPs, which we define as “biological” herein, dominated the population active at −5 to −20°C, while non-heat-labile organic INPs (decomposed by peroxide) dominated at lower temperatures, from −20 to −28°C. Inorganic INPs (remaining after peroxide digestion), were minor contributors to the overall INP activity. Biological INP concentration active around −12°C peaked during rain events and under high relative humidity, reflecting emission mechanisms independent of the background aerosol concentration. The ratio of non-heat-labile organic and inorganic INPs was generally constant, suggesting they originated from the same source, presumably from regional arable topsoil based on air mass histories. Single particle mass spectrometry showed that soil particles aerosolized from a regionally common agricultural topsoil contained known mineral INP sources (K-feldspar and illite) as well as a significant organic component. The INP activity observed in this study correlates well with agricultural soil INP activities from this and other regions of the world, suggesting that the observed INP spectra might be typical of many arable landscapes. These results demonstrate the strong influence of regional continental landscapes, emitting INPs of types that are not yet well represented in global models., Journal of Geophysical Research: Atmospheres, 126 (23), ISSN:0148-0227, ISSN:2169-897X

Levoglucosan has been extensively used as a molecular marker of biomass burning in source-apportionment studies over the last few decades. However, recent studies suggest that the atmospheric lifetime of levoglucosan may be in the order of only 1–2 days under summertime conditions relevant to prescribed/wildfires. Implications of levoglucosan reactivity to wintertime conditions, however, remain uncertain despite significant contributions of domestic wood combustion to wintertime air quality. This study presents smog chamber experiments to investigate levoglucosan decay during photo-oxidation of wood smoke over a temperature range between −8 and 10 °C. Significant decay in particle wall-loss corrected levoglucosan is only observed around 10 °C in these experiments. Theoretical analysis shows that the apparent chemical lifetime of levoglucosan increases at lower temperatures as well as at higher organic aerosol mass concentrations as a result of smaller vapor fractions. The chemical lifetime of a molecular marker is commonly interpreted by a relationship between relative decay in particle wall-loss corrected marker concentrations versus integrated OH exposure. However, this relationship strongly depends on vapor wall-loss rates in addition to temperature, organic aerosol concentrations, and OH concentrations. Therefore, inferred lifetimes from a small set of experiments from a single chamber cannot easily be generalized for the full range of atmospheric smoke conditions.

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.

Solar radiation is the ultimate source of energy for all atmospheric motions. The visible wavelength range of solar radiation represents a significant contribution to the Earth’s energy budget and visible light is a vital indicator for the composition and thermodynamic processes of the atmosphere from the smallest weather to the largest climate scales. The accurate and fast description of light propagation in the atmosphere and its lower boundary environment is therefore of critical importance for the simulation and prediction of weather and climate. Simulated Weather Imagery (SWIm) is a new, fast and physically based visible wavelength 3-dimensional radiative transfer model. Given the location and intensity of the sources of light (natural or artificial) and the composition (e.g., clear or turbid air with aerosols, liquid or ice clouds, and precipitating rain, snow, or ice hydrometeors) of the atmosphere, it describes the propagation of light and produces visually and physically realistic hemispheric or 360° spherical panoramic color images of the atmosphere and the underlying terrain from any specified vantage point either on or above the Earth's surface. Applications of SWIm include the visualization of atmospheric and land surface conditions simulated or forecast by numerical weather or climate analysis and prediction systems for either scientific or lay audiences. Simulated SWim imagery can also be generated for and compared with observed camera images to (i) assess the fidelity, (ii) and improve the performance of numerical atmospheric and land surface models, as well as (iii) through their inclusion into an observational data assimilation scheme, improve the estimate of the state of atmospheric and land surface initial conditions for situational awareness and NWP forecast initialization applications.

Ambient air samples were obtained in Riyadh, the capital and largest city of Saudi Arabia, during two measurement campaigns spanning September 2011 to September 2012. Sixteen particle-phase polycyclic aromatic hydrocarbons (PAH) were quantified in 167 samples. Pyrene and fluoranthene were the most abundant PAH, with average of 3.37 ± 14.01 ng m−3 and 8.00 ± 44.09 ng m−3, respectively. A dominant contribution from low molecular weight (LMW) PAH (MW

Strongly coupled data assimilation frameworks provide a mechanism for including additional information about aerosols through the coupling between aerosol and atmospheric variables, effectively utilizing atmospheric observations to change the aerosol analysis. Here, we investigate the impact of these observations on aerosol using the Maximum Likelihood Ensemble Filter (MLEF) algorithm with Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) which includes the Godard Chemistry Aerosol Radiation and Transport (GOCART) module. We apply this methodology to a dust storm event over the Arabian Peninsula and examine in detail the error covariance and in particular the impact of atmospheric observations on improving the aerosol initial conditions. The assimilated observations include conventional atmospheric observations and Aerosol Optical Depth (AOD) retrievals. Results indicate a positive impact of using strongly coupled data assimilation and atmospheric observations on the aerosol initial conditions, quantified using Degrees of Freedom for Signal.

The use of dust erodible fraction geographical databases in case-study numerical simulations provides more realistic dust loading compared to idealized, non-spatially-constrained methods. Idealized lofting in case study scenarios tends to generate unrealistically large amounts of dust compared to observations, due to the lack of locational constraints. Generally, simulations of enhanced dust mass via surface lofting lead to reductions in daytime insolation due to aerosol scattering effects, as well as reductions in nighttime radiative cooling due to aerosol absorption effects. In simulations with extreme dust concentrations, these effects noticeably suppress the model environment’s diurnal temperature range. In simulations with lesser amounts of lofted dust, the presence of dust is shown to still strongly impact the radiative fluxes while only marginally modifying the low-level temperature. Increased resolution in dust erodible fraction inventories are shown to enhance the details of dust lofting locations and potential, thereby, mitigate over-lofting and associated radiative response biases over regions that are unlikely source locations.

The Regional Atmospheric Modeling System (RAMS) has been interfaced with the Maximum Likelihood Ensemble Filter (MLEF) with the goal of improving initial conditions for aerosol weather forecasting via atmosphere-aerosol coupled data assimilation (RAMS-MLEF). In order to assimilate satellite retrieved aerosol optical depth (AOD), an AOD observation operator customized for the RAMS aerosol module is implemented. Two MLEF-RAMS experiments are carried out for a dust storm event over the Arabian Peninsula that occurred on 4 August 2016. In the first experiment, conventional atmospheric observations from the National Centre for Environmental Prediction (NCEP) Prepared Binary Universal Form for the Representation of meteorological data (PrepBUFR) dataset are assimilated (ATMONLY), while both the atmospheric observations and AOD retrievals from Moderate Resolution Imaging Spectroradiometer (MODIS) are assimilated in the second experiment (ATMAOD). In the two experiments, a list of control variables is used and it includes the three-dimensional wind components, perturbation Exner function, ice-liquid water potential temperature, total water mass mixing ratio, and the two dust modes from the aerosol module. Results indicate that the assimilation of MODIS AOD retrievals improves the representation of the dust plume over Persian Gulf, however, has no obvious impact on the dust plume interior of Saudi Arabia. Such finding is further supported by the examination of analysis increments of some control variables and the information measure in terms of degrees of freedom for signal. This is likely due to the lack of AOD retrievals interior of the Arabian Peninsula. Finally, a 12-h forecast initialized from both experiments is conducted. In general, ATMAOD forecast better represents the Persian Plume but performs poorly for the Saudi Plume, when verified against the aerosol reanalysis product from the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) dataset.

Accurate prediction and representation of three-dimensional aerosol distributions in the littoral (coastal) zone is both desired and difficult with many compounding factors contributing to this problem. To reduce uncertainty in forecasting in coastal regions, a coupled meteorological-aerosol data assimimilation (DA) system has been configured to include satellite observations of aerosol optical depth (AOD). These high-resolution observations are from newly-devised retrieval algorithms that utilize Moderate Resolution Imaging Spectroradiometer (MODIS) data to retrieve AOD over the coastal and turbid water surface. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) is combined with an ensemble-based DA system, the Maximum Likelihood Ensemble Filter (MLEF), to simulate a dust event over the Arabian Peninsula from 2016. The assimimilation of AOD observations required the development of a forward operator that converts model predictions into observation space. This operator, which incorporates hygroscopic growth of aerosol particles and determines extinction efficiency based via Mie theory, has a positive bias between the model guess and the retrieved AOD observations. In order to reduce this bias two different methods are proposed and evaluated. One is a moving average method employed throughout the case study while the other relies on a statistical re-sampling approach. The conclusion of these experiments, determined by a number of metrics including, but not limited to, root mean square (RMS) errors, an evaluation of the reduction in the cost function, and degrees of freedom for signal (DFS), indicate that the bias reduction scheme that accumulates bias information throughout the case study outperforms the method based on re-sampling. This conclusion is corroborated by inspection of the analysis increments from the DA process and by the innovations in observational space. An analysis of the non-Gaussian innovations resulting from the non-linear forward operator is also presented. This research is in support of a Multidisciplinary University Research Initiative (MURI) supported by the Office of Naval Research (ONR) with the primary goal of understanding aerosols in the littoral zone.

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.

Knowledge of the sources of carbonaceous aerosol affecting air quality in Riyadh, Saudi Arabia, is limited but needed for the development of pollution control strategies. We conducted sampling of PM2.5 from April to September 2012 at various sites in the city and used a thermo-optical semi-continuous method to quantify the organic carbon (OC) and elemental carbon (EC) concentrations. The average OC and EC concentrations were 4.7 ± 4.4 and 2.1 ± 2.5 µg m−3, respectively, during this period. Both OC and EC concentrations had strong diurnal variations, with peaks at 06:00–08:00 LT and 20:00–22:00 LT, attributed to the combined effect of increased vehicle emissions during rush hour and the shallow boundary layer in the early morning and at night. This finding suggested a significant influence of local vehicular emissions on OC and EC. The OC ∕ EC ratio in primary emissions was estimated to be 1.01, close to documented values for diesel emissions. Estimated primary organic carbon (POC) and secondary organic carbon (SOC) concentrations were comparable, with average concentrations of 2.0 ± 2.4 and 2.8 ± 3.4 µg m−3, respectively. We also collected 24 h samples of PM10 onto quartz microfiber filters and analyzed these for an array of metals by inductively coupled plasma atomic emission spectroscopy (ICP-AES). Total OC was correlated with Ca (R2 of 0.63), suggesting that OC precursors and Ca may have similar sources, and the possibility that they underwent similar atmospheric processing. In addition to a ubiquitous dust source, Ca is emitted during desalting processes in the numerous refineries in the region and from cement kilns, suggesting these sources may also contribute to observed OC concentrations in Riyadh. Concentration weighted trajectory (CWT) analysis showed that high OC and EC concentrations were associated with air masses arriving from the Persian Gulf and the region around Baghdad, locations with high densities of oil fields and refineries as well as a large Saudi Arabian cement plant. We further applied positive matrix factorization to the aligned dataset of EC, OC, and metal concentrations (Al, Ca, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, and V). Three factors were derived and were proposed to be associated with oil combustion, industrial emissions (Pb based), and a combined source from oil fields, cement production, and local vehicular emissions. The dominant OC and EC source was the combined source, contributing 3.9 µg m−3 (80 %) to observed OC and 1.9 µg m−3 (92 %) to observed EC.

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 microphysics 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 BC 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.

Hourly measurements of elemental carbon (EC) and organic carbon (OC) were made at Mong Kok, a roadside air quality monitoring station in Hong Kong, for a year, from May 2011 to April 2012. The monthly average EC concentrations were 3.8–4.9 μg C m−3, accounting for 9.2–17.7% of the PM2.5 mass (21.5–49.7 μg m−3). The EC concentrations showed little seasonal variation and peaked twice daily, coinciding with the traffic rush hours of a day. Strong correlations were found between EC and NOx concentrations, especially during the rush hours in the morning, confirming vehicular emissions as the dominant source of EC at this site. The analysis by means of the minimum OC / EC ratio approach to determine the OC / EC ratio representative of primary vehicular emissions yields a value of 0.5 for (OC / EC)vehicle. By applying the derived (OC / EC)vehicle ratio to the data set, the monthly average vehicle-related OC was estimated to account for 17–64% of the measured OC throughout the year. Vehicle-related OC was also estimated using receptor modeling of a combined data set of hourly NOx, OC, EC and volatile organic compounds characteristic of different types of vehicular emissions. The OCvehicle estimations by the two different approaches were in good agreement. When both EC and vehicle-derived organic matter (OM) (assuming an OM-to-OC ratio of 1.4) are considered, vehicular carbonaceous aerosols contributed ~ 7.3 μg m−3 to PM2.5, accounting for ~ 20% of PM2.5 mass (38.3 μg m−3) during winter, when Hong Kong received significant influence of air pollutants transported from outside, and ~ 30% of PM2.5 mass (28.2 μg m−3) during summertime, when local emission sources were dominant. A reduction of 3.8 μg m−3 in vehicular carbonaceous aerosols was estimated during 07:00–11:00 (i.e., rush hours on weekdays) on Sundays and public holidays. This could mainly be attributed to less on-road public transportation (e.g., diesel-powered buses) in comparison with non-holidays. These multiple lines of evidence confirm local vehicular emissions as an important source of PM2.5 in an urban roadside environment and suggest the importance of vehicular emission control in reducing exposure to PM2.5 in busy roadside environments.

Size distribution data of major aerosol constituents are essential in source apportioning of visibility degradation, testing and verification of air quality models incorporating aerosols. We report here 1-year observations of mass size distributions of major inorganic ions (sulfate, nitrate, chloride, ammonium, sodium, potassium, magnesium and calcium) and oxalate at a coastal suburban receptor site in Hong Kong, China. A total of 43 sets of size-segregated samples in the size range of 0.056–18 μm were collected from March 2011 to February 2012. The size distributions of sulfate, ammonium, potassium and oxalate were characterized by a dominant droplet mode with a mass mean aerodynamic diameter (MMAD) in the range of ~ 0.7–0.9 μm. Oxalate had a slightly larger MMAD than sulfate on days with temperatures above 22 °C as a result of the process of volatilization and repartitioning. Nitrate was mostly dominated by the coarse mode but enhanced presence in fine mode was detected on winter days with lower temperature and lower concentrations of sea salt and soil particles. This data set reveals an inversely proportional relationship between the fraction of nitrate in the fine mode and product of the sum of sodium and calcium in equivalent concentrations and the dissociation constant of ammonium nitrate (i.e., (1/([Na+] + 2[Ca2+]) × (1/Ke')) when Pn_fine is significant (> 10%). The seasonal variation observed for sea salt aerosol abundance, with lower values in summer and winter, is possibly linked with the lower marine salinities in these two seasons. Positive matrix factorization was applied to estimate the relative contributions of local formation and transport to the observed ambient sulfate level through the use of the combined data sets of size-segregated sulfate and select gaseous air pollutants. On average, the regional/super-regional transport of air pollutants was the dominant source at this receptor site, especially on high-sulfate days while local formation processes contributed approximately 30% of the total sulfate. This work provides field-measurement-based evidence important for understanding both local photochemistry and regional/super-regional transport in order to properly simulate sulfate aerosols in air quality models.

PM2.5 filter sampling was conducted on a daily basis at the HKUST Air Quality Research Supersite (AQRS) for one year from March 2011 to February 2012. Approximately one fifth of the filter samples were subjected to full chemical analysis including major ions, elements, organic carbon (OC), elemental carbon (EC), and non-polar organic compounds (NPOCs). The major ions (sulfate, nitrate, and ammonium) were compared with those measured online by a MARGA system and the two sets of data were found in agreement within 25% or better. The major PM2.5 components (crustal materials, organic matter, soot, ammonium sulfate, ammonium nitrate, and non-crustal trace elements) accounted for 90% of the measured mass with sulfate being the most abundant (32.0%), followed by organic matter (23.5%) and ammonium (11.8%). The monthly variation patterns for different components suggested variable regional/super-regional sources, reflecting variation of transport contribution caused by shifts in synoptic weather conditions. Receptor modeling analysis by Positive Matrix Factorization revealed that secondary sulfate formation process (annual average of 31%), biomass burning (23%), and secondary nitrate formation process (13%) were the three dominant contributing sources to the observed PM2.5 at HKUST AQRS throughout the sampling year. The PM2.5 mass concentrations of all the individual sampling days were within the recently-proposed AQOs standards by the Hong Kong government (35 µg/m 3 for annual average and 75 µg/m 3 for 24-hr average) while approx. 52% of the sampling days were recorded with PM2.5 concentrations exceeding the WHO health 24-hr standards of 25 µg/m 3 . Major composition and source analysis showed that the increased mass concentrations on high PM days were mainly caused by air pollutant transport from the outside-Hong Kong regions. Results from this study indicate the importance of regional/super-regional strategies such as reduction in SO2, NO2 (precursors for secondary inorganic aerosols) and restricting biomass burning for lowering PM2.5 in Hong Kong.

Seasonal variations in light extinction over Hong Kong and the Pearl River Delta (PRD) region in China in January, April, July and October of 2006 were studied using the MM5–CMAQ modeling system. A local empirical visibility regression formula, based on that used in the IMPROVE project ( Malm et al., 1994 ), was introduced to examine the relationship between the predicted aerosol mass concentration and light extinction over the PRD region. The modeling system was able to reproduce the seasonal variations in sulfate, elementary carbon (EC), organic carbon (OC) and PM2.5 mass concentrations, but not aerosol nitrate. Compared to the IMPROVE formula, the local regression formula produced a more accurate prediction of the variation in seasonal light extinction over the inland PRD region, with a 13–27% improvement in model performance according to the normalized mean bias. The seasonal light extinction budget analysis suggested that hydrophilic sulfate, EC, and aged OC are the major contributors to regional visibility degradation over Hong Kong and the PRD. An emission reduction case study also suggested the importance of controlling vehicle and marine vessel emissions to improve regional visibility.

Secondary organic aerosol (SOA) is one of the major components of aerosols in the atmosphere and has not been well understood so far. Due to the complex chemical composition of organic aerosols, the identification of SOA has been a hotspot and difficult issue in the field of aerosol study. This study attempts to quantitatively identify SOA in winter, Shenzhen based on positive matrix factorization (PMF) analysis. Major sources were resolved and SOA were identified subsequently according to the characteristic ion fragments measured by highly time-resolved Aerosol Mass Spectrometer measurement. It showed that in the winter of Shenzhen the average SOA concentration was 9.41±6.33 μg/m3, accounting for 39.9±21.8% of the total organic mass. Compared with primary organic aerosol (POA), the SOA concentrations had no large variation, suggestive of characteristics of regional secondary pollutants. The ratio of SOA/BC had pronounced diurnal variation, similar to that of Ox (O3 + NO2), indicating SOA formation was significantly controlled by activity of photochemistry in the atmosphere. The most effective period for SOA formation was from 9 am–3 pm since the SOA/BC ratio increased by 122% during this period. This study provides a new technical method and a new idea for SOA investigation.

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 underestimates 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 (36%) was lost during the experiments, and roughly half of this particle organic mass loss was from direct particle wall loss (56% of the loss) with the remainder from evaporation of the particles driven by vapor losses to the walls (44% 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 23% uncertainty to the final particle organic mass remaining in the chamber (relative to base-assumptions 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 64% 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.

Nonpolar organic compounds (NPOCs) in ambient particulate matter (PM) commonly include n-alkanes, branched alkanes, hopanes and steranes, and polycyclic aromatic hydrocarbons (PAHs). The recent development of thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS) has greatly reduced time and labor in their quantification by eliminating the laborious solvent extraction and sample concentration steps in the traditional approach that relies on solvent extraction. The simplicity of the TD-GCMS methods has afforded us concentration data of NPOCs in more than 90 aerosol samples in two aerosol field studies and 20 vehicular emissions-dominated source samples in Hong Kong over the past few years. In this work, we examine the interspecies relationships between select NPOCs and their concentration ratios to elemental carbon (EC) among the ambient samples and among the source samples. Our analysis indicates that hopanes were mainly from vehicular emissions and they were significantly oxidized in ambient PM. The hopane/EC ratio in ambient samples was on average less than half of the ratio in vehicular emissions-dominated source samples. This highlights the necessity in considering oxidation loss in applying organic tracer data in source apportionment studies. Select PAH/EC ratio–ratio plots reveal that PAHs had diverse sources and vehicular emissions were unlikely a dominant source for PAHs in Hong Kong. Biomass burning and other regional sources likely dominated ambient PAHs in Hong Kong.

[1] The major inorganic constituents and organic tracer compounds in PM2.5 were used in positive matrix factorization (PMF) and chemical mass balance (CMB) models to apportion the primary and secondary source contributions to organic carbon (OC) in Hong Kong during the summer of 2006. Secondary organic aerosol (SOA) tracers of several biogenic and anthropogenic hydrocarbons were included in the PMF analysis. Their inclusion allowed the identification of two components of SOA among seven factors resolved by PMF. One SOA component was mainly associated with secondary sulfate and nitrate. The other SOA component, characterized by biogenic SOA tracers and mixed with biomass burning and vegetative detritus particles, was biomass burning-induced SOA. Secondary OC (SOC) apportioned by PMF (SOCPMF) was on average 6.84 μgC m−3 (65% of PM2.5 OC) on high pollution days under influence of significant regional transport (i.e., regional days) and 0.70 μgC m−3 (25% of PM2.5 OC) on days under the influence of mainly local emissions (i.e., local days). The biomass burning-induced SOA accounted for 20% of the total SOA on the regional days, underlining the importance of biomass burning aerosol source in this region. The average uncertainty for the SOCPMF estimates was ∼20% on the regional days and ∼120% on the local days. SOCPMF was compared with SOC determined by CMB (SOCCMB, i.e., unapportioned OC by CMB analysis) and a tracer-based method (SOCTBM) that apportioned SOC contributions by four hydrocarbon precursors including isoprene, monoterpenes, β-caryophyllene, and toluene. The three estimates of SOC closely tracked with each other among individual samples. The SOCCMB and SOCPMF estimates on the majority of the regional days differed from each other by less than 25%. Good correlations between contributions of SOC and individual primary OC sources apportioned by PMF and CMB further added to the credence to the PMF-derived estimation of secondary and primary OC source contributions by using secondary and primary aerosol organic tracers as the fitting species.

Oxalic acid is one of the most abundant dicarboxylic acids in the atmosphere, receiving a great deal of attention due to its potential influence on cloud condensation nucleus activities. In this work, we report 10 months of hourly oxalate measurements in particulate matter of less than 2.5 µm in aerodynamic diameter (PM2.5) by a Monitor for Aerosols and Gases in ambient Air at a suburban coastal site in Hong Kong from April 2012 to February 2013. A total of more than 6000 sets of oxalate and inorganic ion data were obtained. The mean (±SD) oxalate concentration was 0.34 (±0.18) µg m−3, accounting for 2.8% of the total ion mass and 1.5% of the PM2.5 mass. Seasonal variation showed higher concentrations in fall and winter (0.54 and 0.36 µg m−3, respectively) and lower concentrations in spring and summer (~0.26 µg m−3). Different from the inorganic ions, a shallow dip in the oxalate concentration consistently occurred in the morning after sunrise (around 9:00 A.M.) throughout all seasons. Our analysis suggests that this was likely due to photolysis of oxalate-Fe (III) complex under sunlight. In summer, a small daytime peak was discernable for oxalate and nitrate. This characteristic, together with a more evident diurnal variation of O3, indicates comparatively more active photochemical oxidation in summer than other seasons. High correlations were observed between oxalate and non-sea-salt SO42− (NSS) (R2 = 0.63) and Ox (O3 + NO2) (R2 = 0.48), indicating significant commonality in their secondary formation. Positive matrix factorization analysis of oxalate and other real-time gas and particle-phase component data estimates that secondary formation processes, including secondary gas or aqueous oxidation processes (49%), oxidation processes of biomass burning emissions (37%), accounted for the majority of PM2.5 oxalate. A backward trajectories cluster analysis found that higher oxalate/NSS ratios were associated with low pollution samples under the influence of marine air masses while the ratios were lower in high pollution samples that were typically associated with continental air masses passing through areas of high anthropogenic emissions. Isolating the “low pollution marine” aerosols across the entire data set indicates that oxalate production increased in the summer compared to other seasons, suggesting either more active marine emissions of oxalate precursors or stronger photochemical processes in the summer.