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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 6-8 a.m. and 20-22 p.m., 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 suggests 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 (POC) and secondary (SOC) organic carbon concentrations were comparable, with average concentrations of 2.0 ± 2.4 and 2.8 ± 3.4 μg m-3, respectively. We also collected 24 hour samples of PM10 onto quartz microfiber filters and analyzed these for an array of metals by ICP-OES. Total OC was correlated with Ca (R2 of 0.63), suggesting they may have similar sources. 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 data set 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. [ABSTRACT FROM AUTHOR]

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 smogchamber 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]