Wanmin Gong

An evaluation of real‐time air quality forecasts and their urban emissions over eastern Texas during the summer of 2006 Second Texas Air Quality Study field study

[1]xa0Forecasts of ozone (O3) and particulate matter (diameter less than 2.5 μm, PM2.5) from seven air quality forecast models (AQFMs) are statistically evaluated against observations collected during August and September of 2006 (49 days) through the Aerometric Information Retrieval Now (AIRNow) network throughout eastern Texas and adjoining states. Ensemble O3 and PM2.5 forecasts created by combining the seven separate forecasts with equal weighting, and simple bias-corrected forecasts, are also evaluated in terms of standard statistical measures, threshold statistics, and variance analysis. For O3 the models and ensemble generally show statistical skill relative to persistence for the entire region, but fail to predict high-O3 events in the Houston region. For PM2.5, none of the models, or ensemble, shows statistical skill, and all but one model have significant low bias. Comprehensive comparisons with the full suite of chemical and aerosol measurements collected aboard the NOAA WP-3 aircraft during the summer 2006 Second Texas Air Quality Study and the Gulf of Mexico Atmospheric Composition and Climate Study (TexAQS II/GoMACCS) field study are performed to help diagnose sources of model bias at the surface. Aircraft flights specifically designed for sampling of Houston and Dallas urban plumes are used to determine model and observed upwind or background biases, and downwind excess concentrations that are used to infer relative emission rates. Relative emissions from the U.S. Environmental Protection Agency 1999 National Emission Inventory (NEI-99) version 3 emissions inventory (used in two of the model forecasts) are evaluated on the basis of comparisons between observed and model concentration difference ratios. Model comparisons demonstrate that concentration difference ratios yield a reasonably accurate measure (within 25%) of relative input emissions. Boundary layer height and wind data are combined with the observed up-wind and downwind concentration differences to estimate absolute emissions. When the NEI-99 inventory is modified to include observed NOy emissions from continuous monitors and expected NOx decreases from mobile sources between 1999 and 2006, good agreement is found with those derived from the observations for both Houston and Dallas. However, the emission inventories consistently overpredict the ratio of CO to NOy. The ratios of ethylene and aromatics to NOy are reasonably consistent with observations over Dallas, but are significantly underpredicted for Houston. Excess ratios of PM2.5 to NOy reasonably match observations for most models but the organic carbon fraction of PM2.5 is significantly underpredicted, pointing to compensating error between secondary organic aerosol (SOA) formation and primary emissions within the models photochemistry and emissions. Rapid SOA formation associated with both Houston and Dallas is inferred to occur within 1 to 3 h downwind of the urban centers, and none of the models reproduce this feature.

Simulation of entrainment and transport of dust particles within North America in April 2001 (“Red Dust Episode”)

[1]xa0A size-resolved, multicomponent, regional-scale particulate-matter (PM) model named AURAMS (A Unified Regional Air-quality Modelling System) has been used to study the entrainment and transport of dust from the southwestern United States and northwestern Mexico to eastern North America during the so-called “Red Dust Episode” in April, 2001. Two different wind-blown-dust emission schemes, the Marticorena-Bergametti-Alfaro (MBA) scheme and the Shao scheme, were incorporated into AURAMS to simulate dust generation, and sensitivity analyses for various dust-emission-scheme parameters were performed. Comparison of the model results with satellite observations and surface measurements showed that the model simulation reasonably reproduced the temporal and spatial distribution of wind-blown dust particles during the episode period in the downwind area of Oklahoma but not in the source region. Both dust-emission schemes captured the main features of the dust transport. The dust-emission-scheme parameter most responsible for inaccurate prediction of wind-blown-dust emission in the source region in this study appeared to be soil moisture content. The soil grain size distribution and the soil plastic pressure were also shown to be important parameters that should be accurately estimated for better model performance. For further validation and reliable use of wind-blown-dust emission schemes, accurate field and remote sensing measurements of those parameters are imperative. The unusually fast transport of dust during the episode appeared to be due to vigorous vertical mixing and uplift of emitted dust. Appropriate parameterization of additional vertical mixing by sub-grid-scale convection may help to better predict the long-range transport of dust storms.

Investigation of carbonyls in cloudwater during ICARTT

[1]xa0Air borne measurements carried out in the summer of 2004 in the lower Great Lakes region as part of the ICARTT 2004 study are used to examine the effects of clouds on the carbonyls in the atmosphere. Concentrations of seven carbonyl species in bulk cloudwater samples were measured with concurrent gas phase HCHO measurements. In the cloudwater, the most abundant carbonyl was HCHO with a median value of 11.9 μmol L−1, followed by acetaldehyde (4.3 μmol L−1), acetone (1.9 μmol L−1), pentanal (1.4 μmol L−1), benzaldehyde (0.5 μmol L−1), butanal (0.4 μmol L−1), and propanal (0.2 μmol L−1). The relative abundance of propanal to acetaldehyde in the cloudwater was substantially lower than estimates from primary emissions. The cloudwater abundance of HCHO relative to the sum of the other carbonyls was found to increase with altitude in the clouds that penetrated the boundary layer. During most flights, the total in-cloud HCHOt (cloudwater + interstitial gas phase) was similar to cloud base HCHOg, suggesting that HCHO was distributed between the two phases through partitioning governed by Henrys law. However, during at least one flight, HCHOt was significantly depleted in the cloud. Finally, the equilibrium gas phase mixing ratios predicted from the cloudwater for all carbonyls but HCHO were much higher than previously measured in the gas phase.

Evaluation of modeled cloud properties against aircraft observations for air quality applications

[1]xa0Cloud microphysical properties are critical for simulating cloud processing of gases and aerosols in air quality models. In this study, cloud liquid water contents (LWC) predicted from a meteorological model at two horizontal resolutions (15 and 2.5 km) are evaluated against aircraft observations during the 2004 International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) campaign. A point-by-point comparison along flight tracks shows good model-observation correlation for temperature and humidity but poor correlation for LWC due to the mismatch in timing and positioning of the clouds between model simulations and observations. Thus a statistical approach is used to compare properties of modeled and observed clouds over the flight domain. The model captures the observed vertical variation of LWC for the towering cumulus (TCu) cases and reproduces the observed variation of LWC from flight to flight independent of cloud types. The model is able to distinguish the difference in the mean and standard deviation of LWC between stratocumulus (SCu) and TCu. However, the “in-cloud” LWC values were generally overpredicted by the model at both resolutions. For SCu, the overprediction is 99% and 45% for the 15- and 2.5-km resolution simulations, respectively, while the overprediction for TCu is slightly smaller at 74% for the 15-km resolution and 24% for the 2.5-km resolution model simulations. The SCu observations were scaled up to enable comparisons at the model-grid scales for these flights. This comparison also shows overpredictions of LWC by the model, although the overprediction is smaller for the model at 15-km resolution.

Comparative Evaluation of Model Simulations of Regional Ozone and Particulate Matters for Two Distinct Summers over Eastern North America

The Environment Canada regional air quality modelling system, AURAMS, is used to simulate two summer periods in 2004 and 2007, coinciding with two air quality measurement campaigns over eastern North America. The two summers are quite distinct in weather and air quality conditions. The model results are compared with various surface based monitoring air and precipitation chemistry measurements to examine model’s capability in capturing the impact of meteorology on air quality and explore the roles of different processes affecting ozone and PM in the region.

Impact of Aerosol Activation on Modelled Regional Particulate Matter Mass and Size Distribution Due to Cloud Processing

Aerosol activation is a key process in aerosol-AQ cloud interaction. Although it is widely studied within the climate modeling community it has not been attracting significant attention within the air quality modeling community. In this study an off-line, sectional, chemically-speciated regional air quality model, AURAMS, has been used to assess the impact of aerosol activation on the modelled regional particulate matter (PM) mass concentration and size distribution. Asimple activation scheme based on an empirical relationship between cloud droplet number density and aerosol number density is compared to a more physically-based activation scheme. Model simulations were compared to aircraft observations obtained during the 2004 ICARTT field campaign. Modelled aerosol light extinction and column aerosol optical depth (AOD) were computed in three different ways in the current study. Two of them based on Mie calculations and one empirical reconstructed mass extinction method. The magnitude of the modeled AOD varies significantly depending on the approach. The impact of different aerosol activation schemes on the modelled AOD in this case is generally in the range of 20–30 % for the two Mie methods. As the empirical reconstructed mass extinction method is not size dependent, it is less sensitive to aerosol activation.

High Resolution Nested Runs of the AURAMS Model with Comparisons to PrAIRie2005 Field Study Data

The PrAIRie2005 campaign took place in the summer of 2005 in the city of Edmonton, Alberta. The measurement campaign was designed and led by air-quality modellers with the scientific objective of determining the extent to which air pollution events in the city are the result of locally emissions versus long-range transport. A nested version of the AURAMS model was constructed for post-campaign simulations and evaluation against the measurement data. The nested model runs at different resolutions, the highest of which is a 3 km horizontal resolution centered on the urban area.

A Process Analysis of the Impact of Air-Quality/Weather Feedbacks Using GEM-MACH

Environment Canada’s “Global Environmental Multiscale – Modelling Air-quality and Chemistry” (GEM-MACH) is the Canadian operational air-quality model, used to provide forecasts of ozone, PM2.5 and air-quality health metrics to the Canadian public. The operational GEM-MACH is an on-line model, but is not fully coupled, in that the chemical variables are not used to modify the weather. The model was converted to fully coupled status as part of Environment Canada’s participation in phase 2 of the Air-Quality Model Evaluation International Initiative, with three classes of modifications: (1) Additions required in order to allow feedbacks to take place between weather and chemistry; (2) Model improvements necessary to ensure feedback accuracy; (3) Model improvements to allow the use of AQMEII-2 prescribed inputs and diagnostic outputs.

Improvements to Wintertime Particulate-Matter Forecasting With GEM-MACH15

Elevated levels of PM2.5 have been observed in North America in all seasons, underlining the need for year-round air-quality (AQ) forecasts. Wintertime AQ forecasting, however, poses unique challenges given well-known seasonal variations in emissions, meteorology, chemistry, and removal processes. In the case of PM2.5, both systematic and episodic overpredictions have been noted in the wintertime for current AQ forecast models, including Environment Canada’s GEM-MACH15 AQ forecast model. GEM-MACH15 is the regional forecasting configuration of the multi-scale, in-line AQ model GEM-MACH. Performance evaluations of GEM-MACH15 predictions for several recent winter periods have pointed to several sources of forecast error, including the spatial and temporal allocation of primary PM2.5 emissions and the treatment of vertical diffusion. This paper describes recent improvements to input emissions for the GEM-MACH15 modelling system and their resulting impacts on forecast performance.