Air quality analyses for permitting new pollution sources often involve modeling dispersion of pollutants using models such as AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model). Representative background pollutant concentrations must be added to modeled concentrations to determine compliance with air quality standards. Summing 98th (or 99th) percentiles of two independent distributions that are unpaired in time overestimates air quality impacts and could needlessly burden sources with restrictive permit conditions. This problem is exacerbated when emissions and background concentrations peak during different seasons. Existing methods addressing this matter either require much input data, or disregard source and background seasonality, or disregard the variability of the background by utilizing a single concentration for each season, month, hour-of-day, day-of-week, or wind direction. Availability of representative background concentrations are another limitation. Here the authors report on work to improve permitting analyses, with the development of (1) daily gridded, background concentrations interpolated from 12-km CMAQ (Community Multiscale Air Quality Model) forecasts and monitored data. A two-step interpolation reproduced measured background concentrations to within 6.2%; and (2) a Monte Carlo (MC) method to combine AERMOD output and background concentrations while respecting their seasonality. The MC method randomly combines, with replacement, data from the same months and calculates 1000 estimates of the 98th or 99th percentiles. The design concentration of background + new source is the median of these 1000 estimates. It was found that the AERMOD design value (DV) + background DV lay at the upper end of the distribution of these one thousand 99th percentiles, whereas measured DVs were at the lower end. This MC method sits between these two metrics and is sufficiently protective of public health in that it overestimates design concentrations somewhat. The authors also calculated probabilities of exceeding specified thresholds at each receptor, better informing decision makers of new source air quality impacts. The MC method is executed with an R script, which is available freely upon request.IMPLICATIONS:Summing representative background pollutant concentrations with air dispersion model output using a Monte Carlo method that respects the seasonality of each provides for more robust and scientifically defensible air quality analyses in support of permit applications. This work provides applicants a method to demonstrate compliance with National Ambient Air Quality Standards and avoid emission controls that might be based on overly conservative analyses. It also calculates the probability of exceeding the standard, allowing regulators to make more informed permitting decisions.

The Community Multi-Scale Air Quality (CMAQ) modeling system was used to investigate ozone and aerosol concentrations in the Pacific Northwest (PNW) during hot summertime conditions during July 1-15, 1996. Two emission inventories (El) were developed: emissions for the first El were based upon the National Emission Trend 1996 (NET96) database and the BEIS2 biogenic emission model, and emissions for the second El were developed through a "bottom up" approach that included biogenic emissions obtained from the GLOBEIS model. The two simulations showed that elevated PM2.5 concentrations occurred near and downwind of the Interstate-5 corridor along the foothills of the Cascade Mountains and in forested areas of central Idaho. The relative contributions of organic and inorganic aerosols varied by region, but generally organic aerosols constituted the largest fraction of PM2.5. In wilderness areas near the 1-5 corridor, organic carbon from anthropogenic sources contributed approximately 50% of the total organic carbon with the remainder from biogenic precursors, while in wilderness areas in Idaho, biogenic organic carbon accounted for 80% of the total organic aerosol. Regional analysis of the secondary organic aerosol formation in the Columbia River Gorge, Central Idaho, and the Olympics/Puget Sound showed that the production rate of secondary organic carbon depends on local terpene concentrations and the local oxidizing capacity of the atmosphere, which was strongly influenced by anthropogenic emissions. Comparison with observations from 12 IMPROVE sites and 21 ozone monitoring sites showed that results from the two El simulations generally bracketed the average observed PM parameters and that errors calculated for the model results were within acceptable bounds. Analysis across all statistical parameters indicated that the NW-AIRQUEST El solution performed better at predicting PM2.5, PM1, and beta(ext) even though organic carbon PM was over-predicted, and the NET96 El solution performed better with regard to the inorganic aerosols. For the NW-AIRQUEST El solution, the normalized bias was 30% and the normalized absolute error was 49% for PM2.5 mass. The NW-AIRQUEST solution slightly overestimated peak hourly ozone downwind of urban areas, while the NET96 solution slightly underestimated peak values, and both solutions over-predicted average 03 concentrations across the domain by approximately 6 ppb.

A real-time photochemical air quality forecast system has been implemented for the Puget Sound region to support public awareness of air quality issues. The Air Indicator Report for Public Access and Community Tracking (AIRPACT) forecast system uses daily numerical weather forecasts from the fifth-generation Pennsylvania State University (PSU)–National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) to drive the California Meteorological Model (CALMET)/California photochemistry grid model (CALGRID) Eulerian photochemical modeling suite. Hourly forecasts of ozone and other pollutant concentrations, including primary particulate emissions from diesel sources, are produced for urban Seattle and environs within a gridded domain consisting of 62 × 67 grid cells (4 km × 4 km) with 13 vertical layers. Detailed gridded emission inventories are adjusted dynamically for time of day, day of the week, month, and gridded ambient temperatures to generate requisite emissions. The forecast system also uses hourly pollutant observation data, reported daily, to perform automated evaluations of forecast accuracy. Forecasts and verification results are provided on a daily basis via the Web (see www.airpact.wsu.edu). This paper describes the forecast system and presents preliminary forecast evaluation results from the Pacific Northwest 2001 (PNW2001) field program and from selected months using the routine monitoring network. AIRPACT is unique nationally as the sole numerical modeling system producing daily, year-round, high-resolution regional air quality forecasts with daily verification.

This paper examines the potential of regional environmental prediction by focusing on the local forecasting effort in the Pacific North; west. A consortium of federal, state, and local agencies have funded the development and operation of a multifaceted numerical prediction system centered at the University of Washington that includes atmospheric, hydrologic, and air quality models, the collection of real-time regional weather data sources, and a number of realtime applications using both observations and model output. The manuscript reviews northwest modeling and data collection systems, describes the funding and management system established to support and guide the effort, provides some examples of regional real-time applications, and examines the national implications of regional environmental prediction.

The rapidly growing Cascadia region of the Pacific Northwest consisting of western Washington, Oregon, and southwestern British Columbia, has experienced surface ozone concentrations that exceed federally mandated standards. A modeling system consisting of the prognostic meteorological model known as the Fifth-Generation Pennsylvania State University-National Center for Atmospheric Research Mesosale Model (MM5), the diagnostic meteorological model CALMET, and the photochemical air quality model CALGRID was developed to investigate ozone formation and transport in this region. To address both the complex topography within the model domain and the relatively sparse network of surface and upper-air meteorological observations, MM5 simulations were performed using 4D data assimilation and a relatively high-resolution inner domain (5-km grid). The MM5 results. however, failed to reproduce the observed wind patterns in some portions of the domain. As a result, it was necessary to employ the MM5 solution as the initial-guess wind field for CALMET (also with a 5-km grid). Objective analysis was applied within CALMET to interpolate the predicted winds with available surface observations. This method involved an iterative approach to End the optimal set of weighting factors within CALMET to merge the MM5 solution with the available meteorological observations.The predicted ozone concentration patterns for a July 1996 event were very complex but generally showed areas of maximum ozone (130 ppb) occurring to the south and east of Puget Sound and within and to the south of the Portland area (170 ppb). Widespread ozone buildup does not occur over the course of the episode; rather, the maximum ozone concentration occurs each day downwind of each urban center. There was no evidence for recirculation of pollutants from one day to the next within an urban area. It also does not appear that emissions from one urban center influence the neighboring downwind urban area. The predicted ozone concentrations showed good agreement with observations at the monitors located along the Interstate Highway No. 5 corridor. Model performance was less good at three sites located in regions of complex terrain.