Organic aerosol spatial/temporal patterns: perspectives of measurements and model.

Ambient measurements from SEARCH and model results from CMAQ-MADRID are analyzed side by side for the southeastern United States to understand the strengths and weaknesses of an air quality model in reproducing key spatial and temporal patterns related to organic aerosol (OA), with inferences regarding secondary organic aerosol (SOA). The model predicts a larger difference in OA concentrations between an urban (JST) and a rural site (YRK) than indicated by measurements. Modeled OA concentrations at JST and YRK are more strongly correlated than measurements. On average, models may understate urban OA emissions, while overstating urban SOA production; measurements indicate that SOA production takes place on the regional scale. Modeled diurnal fluctuations for OA are stronger than measured, due partially to overestimations of the temperature dependence parameters (deltaH(vap)) for SOA in the model. Urban-rural differences in the composition of SOA, inferred from the variations of estimated deltaH(vap), are not properly captured by the model, which does not represent multiple generations of SOA or varied reaction pathways as a function of chemical regimes. Model results are hampered by day-of-the-week and diurnal allocation issues related to EC and OA emissions. Top quintile (20%) afternoon OA concentrations are observed in both warm and cold seasons at the urban site. The frequency of high OA in the cold season is overstated in the model. The model predicts the warm vs cold season frequency of elevated OA episodes better at YRK than at JST, suggesting that regional emissions, chemistry, and transport are better simulated than urban processes.

Response of atmospheric particulate matter to changes in precursor emissions: a comparison of three air quality models.

Three mathematical models of air quality (CMAQ, CMAQ-MADRID, and REMSAD) are applied to simulate the response of atmospheric fine particulate matter (PM2.5) concentrations to reductions in the emissions of gaseous precursors for a 10 day period of the July 1999 Southern Oxidants Study (SOS) in Nashville. The models are shown to predict similar directions of the changes in PM2.5 mass and component (sulfate, nitrate, ammonium, and organic compounds) concentrations in response to changes in emissions of sulfur dioxide (SO2), nitrogen oxides (NO(x)), and volatile organic compounds (VOC), except for the effect of SO2 reduction on nitrate and the effect of VOC reduction on PM2.5 mass. Furthermore, in many cases where the directional changes are consistent, the magnitude of the changes are significantly different among models. Examples are the effects of SO2 and NO(x) reductions on nitrate and PM2.5 mass and the effects of VOC reduction on organic compounds, sulfate and nitrate. The spatial resolution significantly influences the results in some cases. Operational model performance for a PM2.5 component appears to provide some useful indication on the reliability of the relative response factors (RRFs) for a change in emissions of a direct precursor, as well as for a change in emissions of a compound that affects this component in an indirect manner, such as via oxidant formation. However, these results need to be confirmed for other conditions and caution is still needed when applying air quality models for the design of emission control strategies. It is advisable to use more than one air quality model (or more than one configuration of a single air quality model) to span the full range of plausible scientific representations of atmospheric processes when investigating future air quality scenarios.

Modeling secondary organic aerosol formation via multiphase partitioning with molecular data.

A new model for atmospheric secondary organic aerosol (SOA) is presented for biogenic compounds. It is based to the extent possible on experimental molecular SOA data, and it is compatible with any existing gas-phase chemical kinetic mechanism. Six SOA precursors or groups of precursors are used to represent biogenic monoterpenes and sesquiterpenes. SOA formation is modeled using five SOA surrogates to represent classes of compounds with different partitioning properties, e.g., hydrophobicity, aqueous solubility, acid dissociation, and saturation vapor pressure. Model simulations are evaluated against smog chamber data for SOA yields and some adjustments are made to uncertain stoichiometric coefficients and saturation vapor pressure parameters to improve model performance. The model is applied undertypical atmospheric conditions to exemplify the effect of relative humidity on SOA formation and the relative contributions of hydrophilic and hydrophobic SOA.

Application and evaluation of two air quality models for particulate matter for a southeastern U.S. episode.

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29-July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O3), particulate matter with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 microm (PM10) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O3 and PM than CMAQ. Both models tend to predict O3 values that are higher than those observed. For observed O3 values above 60 ppb, O3 performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O3 values above 40 ppb. Both models predict similar amounts of sulfate (SO4(2-)) and organic matter, and both predict SO4(2-) to be the largest contributor to PM2.5. PMCAMx generally predicts higher amounts of ammonium (NH4+), nitrate (NO3-), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO3-, NH4+, and BC than observed, which degrades its performance. For PM10 and PM2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37-43% and -33-4% for CMAQ and 50-59% and 7-30% for PMCAMx. Both models predict the largest MNGEs for NO3- (98-104% for CMAQ 138-338% for PMCAMx). The inaccurate NO3- predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.

Regional modeling of the atmospheric fate and transport of benzene and diesel particles.

The Community Multiscale Air Quality model (CMAQ) was modified to simulate the atmospheric fate and transport of benzene and diesel particles. We simulated the July 11-15, 1995 period over a domain covering the eastern United States with a 12-km horizontal resolution and a finer (4 km) resolution over a part of the northeastern United States that includes Washington, DC and New York City. The meteorological fields were obtained from a simulation conducted earlier with the mesoscale model MM5. Gridded emission files for benzene and diesel particles were developed using the SMOKE modeling system. The results of the model simulations showed that benzene concentrations were commensurate with available measurements. Over the 4-km resolution domain, a comparison between simulated and measured 24-h average concentrations showed a fractional error of 0.46, a fractional bias of 0.14, and a coefficient of determination (r2) of 0.25. A comparison between simulated benzene hourly concentrations in New York City and in the Brigantine Wilderness Area, NJ, showed that urban concentrations were greater than the remote area concentrations by a factor of 2-5. The results of the diesel particle simulations showed spatial and temporal patterns that were similar to those obtained for benzene. However, because of the lesser contribution of on-road mobile sources to diesel particle emissions compared to benzene emissions, diesel particle concentrations showed stronger gradients between urban areas and remote areas. A comparison between diesel particle concentrations in New York City and in the Brigantine Wilderness Area, NJ, showed that the urban concentrations were greater than the remote area concentrations by a factor of 2-10. Assuming that diesel particles consist of 50% "elemental" carbon (EC), the simulated EC concentrations were in close agreement (within 10%) with the measured concentration in the urban area (Washington, DC) but were significantly lower than the measured EC concentrations in the remote area (Brigantine Wilderness Area). This result suggests that other sources beside diesel fuel engines contribute to atmospheric EC concentrations and that EC may not be a good surrogate for diesel particles. A comparison of both benzene and diesel particle simulated concentrations between an urban area (New York City) and a remote area (Brigantine Wilderness Area) shows that, at a spatial resolution of 4 km, the regional background may contribute from 10 to 20% to the peak concentrations. These results suggest that the regional background may not be negligible and should be taken into account in urban air toxics studies.

Uncertainties in modeling secondary organic aerosols: three-dimensional modeling studies in Nashville/western Tennessee.

The formation of secondary organic aerosols (SOA) is simulated for the Nashville/western Tennessee domain using three recent SOA modules incorporated into the three-dimensional air quality model, CMAQ. The Odum/Griffin et al. and CMU/STI modules represent SOA absorptive partitioning into a mixture of primary and secondary particulate organic compounds (OC), with some differences in the formulation of the absorption process and the selection of SOA species and their precursors. Empirical representations based on measured laboratory SOA yields are used for condensable organic products in both these modules. The AEC module simulates SOA absorption into organic and aqueous particulate phases, and a representation based on an explicit gas-phase mechanism is used in the AEC module. Predicted SOA concentrations can vary by a factor of 10 or more. In general, the gas-phase mechanistic approach predicts a higher yield of SOA than those based on laboratory yields. There exist some differences in the two empirical modules despite their similar basis on experimental data. All three modules predict a dominance of SOA of biogenic origin as compared to SOA of anthropogenic origin. The causes for differences among the three SOA modules include the representation of terpenes, the mechanistic versus empirical representation of SOA-forming reactions, the identities of SOA, and the parameters used in the gas/particle partitioning calculations. Two sensitivity studies show that formation of water-soluble SOA and temperature dependence may be areas of key uncertainties affecting current models.

Day-of-Week behavior of atmospheric ozone in three U.S. cities.

The weekly cycles of atmospheric ozone (O3) are of interest because they provide information about the response of O3 to changes in anthropogenic emissions from weekdays to weekends. The weekly behavior of O3 in Chicago, IL; Philadelphia, PA; and Atlanta, GA, is contrasted. In Chicago and Philadelphia, maximum 1-hr average O3 increases on weekends. In Atlanta, O3 builds up from Mondays to Fridays and declines during weekends. In all three areas, volatile organic compound (VOC)/nitrogen oxides (NOx) ratios are higher during weekends, resulting from greater than proportionate decreases in NOx relative to VOC emissions. The VOC/NOx ratios correlate with maximum 1-hr O3 concentrations in Chicago, a response consistent with a VOC-sensitive airshed. A weak correlation between O3 concentrations and VOC/NOx ratios in Philadelphia suggests the impact of transported O3, which is formed in upwind VOC-sensitive locations that may be hundreds of kilometers away. Ozone concentrations in Atlanta do not correlate with VOC/NOx ratios but with concentrations of NOx and total reactive nitrogen (NOy) carried over from the previous day. When data from 1986-1990 and 1995-1999 are compared, only small differences in the weekly behavior of O3 are observed in Chicago and Philadelphia. The day-of-week differences in O3 are amplified in the more recent period in Atlanta, a possible result of urban growth.

Contribution of biogenic emissions to the formation of ozone and particulate matter in the eastern United States.

As anthropogenic emissions of ozone (O3) precursors, fine particulate matter (PM2.5), and PM2.5 precursors continue to decrease in the United States, the fraction of O3 and PM2.5 attributable to natural sources may become significant in some locations, reducing the efficacy that can be expected from future controls of anthropogenic sources. Modeling studies were conducted to estimate the contribution of biogenic emissions to the formation of O3 and PM2.5 in Nashville/TN and the northeastern United States. Two approaches were used to bound the estimates. In an anthropogenic simulation, biogenic emissions and their influence at the domain boundaries were eliminated. Contributions of biogenic compounds to the simulated concentrations of O3 and PM2.5 were determined by the deviation of the concentrations in the anthropogenic case from those in the base case. A biogenic simulation was used to assess the amounts of O3 and PM2.5 produced in an environment free from anthropogenic influences in emissions and boundary conditions. In both locations, the contribution of biogenic emissions to O3 was small (<23%) on a domain-wide basis, despite significant biogenic volatile organic compounds (VOC) emissions (65-89% of total VOC emissions). However, the production of O3 was much more sensitive to biogenic emissions in urban areas (22-34%). Therefore, the effects of biogenic emissions on O3 manifested mostly via their interaction with anthropogenic emissions of NOx. In the anthropogenic simulations, the average contribution of biogenic and natural sources to PM2.5 was estimated at 9% in Nashville/TN and 12% in the northeast domain. Because of the long atmospheric lifetimes of PM2.5, the contribution of biogenic/natural PM2.5 from the boundary conditions was higher than the contribution of biogenic aerosols produced within the domain. The elimination of biogenic emissions also affected the chemistry of other secondary PM2.5 components. Very little PM2.5 was formed in the biogenic simulations.