Abstract. This paper describes the experiences and insights gained from inventory preparation and emissions processing for the Seasonal Model for Regional Air Quality (SMRAQ) project. The emission inventory was derived from the 1990 and 1995 Ozone Transport Assessment Group (OTAG) inventories. Here we outline the emissions processing strategy used for the May-to-September simulation, summarize the inventory characteristics and corrections made on the OTAG inventories, and describe the quality assurance steps taken as part of the processing. We then provide spatial maps and daily total time series charts of the hourly, gridded emissions of nitrogen oxides (NOx), reactive organic gases (ROG), and carbon monoxide (CO). Large peaks from electric utility point sources and urban mobile sources characterize the NOx emissions, and the NOx emissions in nonpeak regions are primarily mobile-source emissions. ROG emissions are dominated by biogenic isoprene production in the southern United States, and they have a strong seasonal variability. CO emissions are characterized by less variability, with area and mobile sources dominating the inventory. We compare ratios of season-average nonmethane organic gases to NOx between the emission inventory and the Photochemical Assessment Monitoring Stations (PAMS) data, and these comparisons show poor correlation between the inventory and ambient ratios.

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[1] The performance of the Multiscale Air Quality Simulation Platform (MAQSIP) in simulating the regional distributions of tropospheric ozone and particulate matter (PM) is evaluated through comparisons of model results from three-dimensional simulations against available surface and aircraft measurements. These applications indicate that the model captures the dynamic range of observations and the spatial trends represented in measurements. Some discrepancies also exist, however, and they are discussed in the context of model formulation, input data specification and assumptions, and variability and bias in measurements. The daily normalized bias (within ±20%) and normalized gross errors (<25%) for predicted surface level O 3 over an entire summer season are within the suggested performance criteria for management evaluation studies and are comparable to, if not smaller than, those reported previously for other regional O 3 models. Comparisons of modeled PM composition with speciated fine particle concentration measurements show that the model is able to capture the spatial variability in fine PM mass as well as in the inorganic component fractions. Both measurements and model results show that in the summertime in the eastern U.S., SO 4 2À is a relatively large component of fine PM mass; in contrast, NO 3 À is a significant fraction in the western U.S. in the wintertime case studied. The ability of the model to simulate the observed visibility indices (extinction coefficient and deciview) are evaluated through comparisons of model estimates using both a detailed Mie theory-based calculation (based on predicted aerosol size and number distributions) and an empirical mass reconstruction algorithm. Both modeled and observed data show that among the various aerosol components, in the eastern U.S. SO 4 2À contributes the largest fraction to the aerosol extinction (35-85%), while organic mass contributes up to 20-25%. In contrast, in the western U.S., SO 4 2À and NO 3 À have comparable contributions (20-50%) to the observed aerosol extinction. Comparisons with limited observational aircraft data, however, show moderate to poor correlation with measurements in the free troposphere. While these discrepancies can be attributed in part to model initialization and lateral boundary conditions specification, there is a need for further evaluation of the representation of boundary layer-free troposphere exchange mechanisms as well as the chemical mechanisms currently used in the model for representing chemistry in the free troposphere.

This article reports on the first implementation of a real-time Eulerian photochemical model f o recast system in the United States. The forecast system consists of a tripartite set of one-way coupled models that run routinely on a parallel micro process or supercomputer. The component models are the fifth-generation Pennsylvania State University (PSU)–NCAR Mesoscale Model (MM5), the Sparse-Matrix Operator Kernel for Emissions (SMOKE) model, and the Multiscale Air Quality Simulation Platform—Real Time (MAQSIPRT) photochemical model. Though the system has been run in real time since the summer of 1998, forecast results obtained during August of 2001 at 15-km grid spacing over New England and the northern mid-Atlantic—conducted as part of an “early start” NOAA air quality forecasting initiative—are described in this article.The development and deployment of a real-time numerical air quality prediction (NAQP) system is technically challenging. MAQSIP-RT contains a full photochemical oxidant gas-phase chemical mechanism together with transport, dry deposition, and sophisticated cloud treatment. To enable the NAQP system to run fast enough to meet operational forecast deadlines, significant work was devoted to data flow design and software engineering of the models and control codes. The result is a turnkey system now in use by a number of agencies concerned with operational ozone forecasting.Results of the chosen episode are compared against three other models/modeling techniques: a traditional statistical model used routinely in the metropolitan Philadelphia, Pennsylvania, area, a set of publicly issued forecasts in the northeastern United States, and the operational Canadian Hemispheric and Regional Ozone and NOx System (CHRONOS) model. For the test period it is shown that the NAQP system performs as well or better than all of these operational approaches. Implications for the impending development of an operational U.S. ozone forecasting capability are discussed in light of these results.

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