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A new secondary organic aerosol (SOA) parameterization based on the volatility basis set is implemented in a regional air quality model WRF‐CHEM. Full meteorological and chemistry simulations are carried out for the United States for August–September 2006. Predicted organic aerosol (OA) concentrations are compared against surface measurements made by several networks and aircraft data from the TexAQS‐2006 field campaign. Elemental carbon simulations are also evaluated in order to evaluate the model's ability to capture their emissions, transport, and removal. Certain measurement limitations, such as daily averaged OA concentrations, impose some difficulties on the model evaluation, and hourly averaged OA measurements provide more informative constraints compared to daily concentrations. The updated model demonstrates a significant improvement in simulating the OA concentrations compared to the standard WRF‐CHEM, which predicts very little SOA. The improvement in organic carbon (OC) predictions is noticeable in correlations and model bias. The correlations of OC exceed that of the persistence forecasts for hourly concentrations in the southeast United States during daytime. The updated traditional SOA yields still lead to an underestimation of observed OA, while addition of the multigenerational volatile organic compound (VOC) oxidation drastically improves model performance. However, several key uncertainties remain in SOA formation and loss mechanisms, which are characterized through several perturbation simulations. Dry deposition of VOC oxidation products is an important factor in the atmospheric SOA budget. The combination of the biogenic VOC emissions, updated SOA yields, and aging mechanism result in biogenic SOA being the dominant OA component for much of the nonurban United States. Key Points VBS approach to secondary organic aerosol formation within WRF‐CHEM Evaluation using surface and aircraft data Organic aerosol modeling for the continental United States

We evaluate the rates of secondary production and primary emission of formaldehyde (CH2O) from petrochemical industrial facilities and on-road vehicles in the Houston Texas region. This evaluation is based upon ambient measurements collected during field studies in 2000, 2006 and 2009. The predominant CH2O source (92 ± 4% of total) is secondary production formed during the atmospheric oxidation of highly reactive volatile organic compounds (HRVOCs) emitted from the petrochemical facilities. Smaller contributions are primary emissions from these facilities (4 ± 2%), and secondary production (~3%) and primary emissions (~1%) from vehicles. The primary emissions from both sectors are well quantified by current emission inventories. Since secondary production dominates, control efforts directed at primary CH2O emissions cannot address the large majority of CH2O sources in the Houston area, although there may still be a role for such efforts. Ongoing efforts to control alkene emissions from the petrochemical facilities, as well as volatile organic compound emissions from the motor vehicle fleet, will effectively reduce the CH2O concentrations in the Houston region. We do not address other emission sectors, such as off-road mobile sources or secondary formation from biogenic hydrocarbons. Previous analyses based on correlations between ambient concentrations of CH2O and various marker species have suggested much larger primary emissions of CH2O, but those results neglect confounding effects of dilution and loss processes, and do not demonstrate the causes of the observed correlations. Similar problems must be suspected in any source apportionment analysis of secondary species based upon correlations of ambient concentrations of pollutants.

A large fraction of atmospheric aerosols are derived from organic compounds with various volatilities. A National Oceanic and Atmospheric Administration (NOAA) WP-3D research aircraft made airborne measurements of the gaseous and aerosol composition of air over the Deepwater Horizon (DWH) oil spill in the Gulf of Mexico that occurred from April to August 2010. A narrow plume of hydrocarbons was observed downwind of DWH that is attributed to the evaporation of fresh oil on the sea surface. A much wider plume with high concentrations of organic aerosol (>25 micrograms per cubic meter) was attributed to the formation of secondary organic aerosol (SOA) from unmeasured, less volatile hydrocarbons that were emitted from a wider area around DWH. These observations provide direct and compelling evidence for the importance of formation of SOA from less volatile hydrocarbons.

Observations from the NOAA WP‐3D aircraft during CalNex in May and June 2010 are used to quantify ammonia (NH3) emissions from automobiles and dairy facilities in the California South Coast Air Basin (SoCAB) and assess their impact on particulate ammonium nitrate (NH4NO3) formation. These airborne measurements in the SoCAB are used to estimate automobile NH3 emissions, 62 ± 24 metric tons day−1, and dairy facility NH3 emissions, 33 ± 16 to 176 ± 88 metric tons day−1. Emission inventories agree with the observed automobile NH3:CO emission ratio, but substantially underpredict dairy facility NH3 emissions. Conditions observed downwind of the dairy facilities were always thermodynamically favorable for NH4NO3 formation due to high NH3 mixing ratios from the concentrated sources. Although automobile emissions generated lower NH3 mixing ratios, they also can thermodynamically favor NH4NO3 formation. As an aerosol control strategy, addressing the dairy NH3 source would have the larger impact on reducing SoCAB NH4NO3 formation. Key Points Mass of SoCAB ammonia emissions is similar from automobile and dairy sources SoCAB dairy ammonia emissions are underrepresented in inventories Dairy ammonia emissions have larger impact on SoCAB ammonium nitrate formation

The performance of different urban surface parameterizations in the WRF (Weather Research and Forecasting) in simulating urban boundary layer (UBL) was investigated using extensive measurements during the Texas Air Quality Study 2006 field campaign. The extensive field measurements collected on surface (meteorological, wind profiler, energy balance flux) sites, a research aircraft, and a research vessel characterized 3-dimensional atmospheric boundary layer structures over the Houston-Galveston Bay area, providing a unique opportunity for the evaluation of the physical parameterizations. The model simulations were performed over the Houston metropolitan area for a summertime period (12–17 August) using a bulk urban parameterization in the Noah land surface model (original LSM), a modified LSM, and a single-layer urban canopy model (UCM). The UCM simulation compared quite well with the observations over the Houston urban areas, reducing the systematic model biases in the original LSM simulation by 1–2 °C in near-surface air temperature and by 200–400 m in UBL height, on average. A more realistic turbulent (sensible and latent heat) energy partitioning contributed to the improvements in the UCM simulation. The original LSM significantly overestimated the sensible heat flux (~200 W m−2) over the urban areas, resulting in warmer and higher UBL. The modified LSM slightly reduced warm and high biases in near-surface air temperature (0.5–1 °C) and UBL height (~100 m) as a result of the effects of urban vegetation. The relatively strong thermal contrast between the Houston area and the water bodies (Galveston Bay and the Gulf of Mexico) in the LSM simulations enhanced the sea/bay breezes, but the model performance in predicting local wind fields was similar among the simulations in terms of statistical evaluations. These results suggest that a proper surface representation (e.g. urban vegetation, surface morphology) and explicit parameterizations of urban physical processes are required for accurate urban atmospheric numerical modeling.

Recently, it has been shown that mass conservation in Lagrangian models is improved by using time-average winds out of Eulerian models. In this study, we evaluate the mass conservation and trajectory uncertainties in complex terrain at mesoscale using the FLEXPART Lagrangian particle dispersion model coupled with the WRF mesoscale model. The specific form of vertical wind used is found to have a large effect. Time average wind with time average sigma dot (σ·), instantaneous wind with geometric cartesian vertical wind (w) and instantaneous wind with σ· are used to simulate mixing ratios of a passive tracer in forward and backward runs using different time interval outputs and horizontal resolutions in California. Mass conservation in the FLEXPART model was not an issue when using time-average wind or instantaneous wind with σ·. However, mass was poorly conserved using instantaneous wind with w, with a typical variation of 25% within 24 h. Uncertainties in surface residence time (a backtrajectory product commonly used in source receptor studies or inverse modeling) calculated for each backtrajectory run were also analyzed. The smallest uncertainties were systematically found when using time-average wind. Uncertainties using instantaneous wind with σ· were slightly larger, as long as the time interval of output was sufficiently small. The largest uncertainties were found when using instantaneous wind with w. Those uncertainties were found to be linearly correlated with the local average gradient of orography. Differences in uncertainty were much smaller when trajectories were calculated over flat terrain. For a typical run at mesoscale in complex terrain, 4 km horizontal resolution and 1 h time interval output, the average uncertainty and bias in surface residence time is, respectively, 8.4% and -2.5% using time-average wind, and 13% and -3.7% using instantaneous wind with σ· in complex terrain. The corresponding values for instantaneous wind with cartesian w were 24% and -11%. While the use of time-average wind systematically improves uncertainty in FLEXPART, the improvements are small, and therfore a systematic use of time-average wind in Lagrangian models is not necessarily required. Use of cartesian vertical wind in complex terrain, however, should be avoided.

Satellite and aircraft observations made during the 2006 Texas Air Quality Study (TexAQS) detected strong urban, industrial and power plant plumes in Texas. We simulated these plumes using the Weather Research and Forecasting-Chemistry (WRF-Chem) model with input from the US EPA's 2005 National Emission Inventory (NEI-2005), in order to evaluate emissions of nitrogen oxides (NOx = NO + NO2 ) and volatile organic compounds (VOCs) in the cities of Houston and Dallas-Fort Worth. We compared the model results with satellite retrievals of tropospheric nitrogen dioxide (NO2 ) columns and airborne in-situ observations of several trace gases including NOx and a number of VOCs. The model and satellite NO2 columns agree well for regions with large power plants and for urban areas that are dominated by mobile sources, such as Dallas. However, in Houston, where significant mobile, industrial, and in-port marine vessel sources contribute to NOx emissions, the model NO2 columns are approximately 50%-70% higher than the satellite columns. Similar conclusions are drawn from comparisons of the model results with the TexAQS 2006 aircraft observations in Dallas and Houston. For Dallas plumes, the model-simulated NO2 showed good agreement with the aircraft observations. In contrast, the model-simulated NO2 is ~60% higher than the aircraft observations in the Houston plumes. Further analysis indicates that the NEI-2005 NOx emissions over the Houston Ship Channel area are overestimated while the urban Houston NOx emissions are reasonably represented. The comparisons of model and aircraft observations confirm that highly reactive VOC emissions originating from industrial sources in Houston are underestimated in NEI-2005. The update of VOC emissions based on Solar Occultation Flux measurements during the field campaign leads to improved model simulations of ethylene, propylene, and formaldehyde. Reducing NOx emissions in the Houston Ship Channel and increasing highly reactive VOC emissions from the point sources in Houston improve the model's capability of simulating ozone (O3 ) plumes observed by the NOAA WP-3D aircraft, although the deficiencies in the model O3 simulations indicate that many challenges remain for a full understanding of the O3 formation mechanisms in Houston.

Texas Air Quality Study field campaigns took place in eastern Texas in August–October of 2000 and 2006. Several flights of NOAA and NCAR research aircraft were dedicated to characterizing anthropogenic emissions over Houston. We present results from an inverse modeling technique that uses three atmospheric transport models and these aircraft observations to assess and improve existing emission inventories. We used inverse modeling techniques to improve the spatial and temporal emissions' distribution of CO, NOy, and SO2 predicted by the 4 km resolution U.S. Environmental Protection Agency (EPA) National Emission Inventory (NEI) for 2005. Differences between the prior and posterior inventories are discussed in detail. In September 2006, we found that the prior daytime CO emissions in the Houston urban area have to be reduced by 41% ± 8%. Over the Houston Ship Channel, where industrial emissions are predominant, the prior emissions have to be decreased by 43% ± 5% for CO and 51% ± 5% for NOy. Prior NOy emissions from other major ports around Houston also have to be reduced, probably owing to uncertain nearshore ship emissions in the EPA NEI inventory. Using the measurements from the two field campaigns, we assessed the emissions' variability between August 2000 and September 2006. Daytime CO emissions from the Houston urban area have decreased by 8% ± 3%, while the NOy emissions have increased by 20% ± 6%. In the Houston Ship Channel, daytime NOy emissions have increased by 13% ± 7%. Our results show qualitative consistencies with known changes in Houston emissions' sources. Key Points Aircraft observations are used to improve emission inventories in Houston Three transport models and two inverse modeling methods used to estimate uncertainties Urban and industrial emission are reduced by 40% and 50% in EPA NEI in Houston

We developed a new inversion method to calculate an emission inventory for an anthropogenic pollutant without a prior emission estimate at mesoscale. This method employs slopes between mixing ratio enhancements of a given pollutant (CO2, for instance) with other co‐emitted tracers in conjunction with the emission inventories of those tracers (CO, NOy, and SO2 are used in this example). The current application of this method employed in situ measurements onboard the NOAA WP‐3 research aircraft during the 2006 Texas Air Quality Study (TexAQS 2006). We used 3 different transport models to estimate the uncertainties introduced by the transport models in the inversion. We demonstrated the validity of the new inversion method by calculating a 4 × 4 km2 emission inventory of anthropogenic CO2 in the Houston area in Texas, and comparing it to the 10 × 10 km2 Vulcan emission inventory for the same region. The calculated anthropogenic CO2 inventory for the Houston Ship Channel, home to numerous major industrial and port emission sources, showed excellent agreement with Vulcan. The daytime CO2 average flux from the Ship Channel is the largest urban CO2 flux reported in the literature. Compared to Vulcan, the daytime urban area CO2 emissions were higher by 37% ± 6%. Those differences can be explained by uncertainties in emission factors in Vulcan and by increased emissions from point sources and on‐road emitters between 2002, the reference year in Vulcan, and 2006, the year that the TexAQS observations were made. Key Points Our new inversion method calculates mesoscale emission inventory without a prior We calculate 4x4km CO2 anthropogenic emission in Houston Results in agreement with 10x10km Vulcan inventory

We describe a new functionality within the Weather Research and Forecasting (WRF) model with coupled Chemistry (WRF-Chem) that allows simulating emission, transport, dispersion, transformation and sedimentation of pollutants released during volcanic activities. Emissions from both an explosive eruption case and a relatively calm degassing situation are considered using the most recent volcanic emission databases. A preprocessor tool provides emission fields and additional information needed to establish the initial three-dimensional cloud umbrella/vertical distribution within the transport model grid, as well as the timing and duration of an eruption. From this source condition, the transport, dispersion and sedimentation of the ash cloud can be realistically simulated by WRF-Chem using its own dynamics and physical parameterization as well as data assimilation. Examples of model applications include a comparison of tephra fall deposits from the 1989 eruption of Mount Redoubt (Alaska) and the dispersion of ash from the 2010 Eyjafjallajökull eruption in Iceland. Both model applications show good coincidence between WRF-Chem and observations.