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This study presents a comparative evaluation of the impact of WRF-NMM and WRFARW meteorology on CMAQ simulations of PM2.5, its composition and related precursors over the eastern United States with the intensive observations obtained by aircraft (NOAA P-3), ship and surface monitoring networks (AIRNow, IMPROVE, CASTNet and STN) during the 2006 TexAQS/GoMACCS study. The results at the AIRNow surface sites show that both ARW-CMAQ and NMM-CMAQ reproduced day-to-day variations of observed PM2.5 and captured the majority of observed PM2.5 within a factor of 2 with a NMB value of -0.4% for ARW-CMAQ and -18% for NMM-CMAQ. Both models performed much better at the urban sites than at the rural sites, with greater underpredictions at the rural sites. Both models consistently underestimated the observed PM2.5 at the rural IMPROVE sites by -1% for the ARW-CMAQ and -19% for the NMM-CMAQ. The greater underestimations of Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed, OC and EC by the NMM-CMAQ contributed to increased underestimation of PM2.5 at the IMPROVE sites. The NMB values for PM2.5 at the STN urban sites are 15% and -16% for the ARW-CMAQ and NMM-CMAQ, respectively. The underestimation of PM2.5 at the STN sites by the NMM-CMAQ mainly results from the underestimations of the Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed and TCM components, whereas the overestimation of PM2.5 at the STN sites by the ARW-CMAQ results from the overestimations of Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed. The comparison with P-3 aircraft measurements reveals that both ARW-CMAQ and NMM-CMAQ have very similar model performance for vertical profiles for PM2.5 chemical components (Due to image rights restrictions, multiple line equation(s) cannot be graphically displayed) and related gaseous species (HNO3, SO2, NH3, isoprene, toluene, terpenes) as both models used the same chemical mechanisms and emissions. The results of ship along the coast of south-eastern Texas over the Gulf of Mexico show that both models captured the temporal variations and broad synoptic change seen in the observed HCHO and acetaldehyde with the means NMB<30% most of the time but they consistently underestimated terpenes, isoprene, toluene and SO2. [ABSTRACT FROM AUTHOR]

The article discusses a research study which examines the effect of a new condensed toluene mechanism on the Community Multiscale Air Quality Modeling system in the U.S. Findings reveal that the toluene mechanism increases predicted ozone in some cities in the country, but it does not improve ozone production efficiency. It suggests that an ozone enhancement can be attained if elevated toluene emissions exist.

This paper discusses the need for critically evaluating regional-scale (~200-2000 km) three-dimensional numerical photochemical air quality modeling systems to establish a model's credibility in simulating the spatio-temporal features embedded in the observations. Because of limitations of currently used approaches for evaluating regional air quality models, a framework for model evaluation is introduced here for determining the suitability of a modeling system for a given application, distinguishing the performance between different models through confidence-testing of model results, guiding model development, and analyzing the impacts of regulatory policy options. The framework identifies operational, diagnostic, dynamic, and probabilistic types of model evaluation. Operational evaluation techniques include statistical and graphical analyses aimed at determining whether model estimates are in agreement with the observations in an overall sense. Diagnostic evaluation focuses on process-oriented analyses to determine whether the individual processes and components of the model system are working correctly, both independently and in combination. Dynamic evaluation assesses the ability of the air quality model to simulate changes in air quality stemming from changes in source emissions and/or meteorology, the principal forces that drive the air quality model. Probabilistic evaluation attempts to assess the confidence that can be placed in model predictions using techniques such as ensemble modeling and Bayesian model averaging. The advantages of these types of model evaluation approaches are discussed in this paper.

A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within +/- 20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites. The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64-77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations.