The University of Colorado Airborne Solar Occultation Flux (CU AirSOF) instrument conducted the first suborbital carbon monoxide (CO) mass flux measurements on the scale of large wildfires, showing that the destructive fires in northern California in October 2017 emitted 2,040 ± 316 tonnes CO hr −1 . Pyrogenic estimates from seven satellite‐based emission inventories bracket the observed flux, but their range spans a factor of 83. The simulated air quality impacts in the form of ozone and fine particulate matter scale primarily with these uncertain emission amounts, and range from insignificant to very severe. This uncertainty in predicting emissions is reduced to a factor of ∼2 by the CU AirSOF flux measurements, with potential for future improvements. The uncertainty is primarily the result of uncertain vegetation types and sources of radiative power measurements, and to a lesser extent uncertain emission factors and fire diurnal cycles.

This paper provides a synthesis of results that have emerged from recent modeling studies of the potential sensitivity of U.S. regional ozone (O3) concentrations to global climate change (ca. 2050). This research has been carried out under the auspices of an ongoing U.S. Environmental Protection Agency (EPA) assessment effort to increase scientific understanding of the multiple complex interactions among climate, emissions, atmospheric chemistry, and air quality. The ultimate goal is to enhance the ability of air quality managers to consider global change in their decisions through improved characterization of the potential effects of global change on air quality, including O3 The results discussed here are interim, representing the first phase of the EPA assessment. The aim in this first phase was to consider the effects of climate change alone on air quality, without accompanying changes in anthropogenic emissions of precursor pollutants. Across all of the modeling experiments carried out by the different groups, simulated global climate change causes increases of a few to several parts per billion (ppb) in summertime mean maximum daily 8-h average O3 concentrations over substantial regions of the country. The different modeling experiments in general do not, however, simulate the same regional patterns of change. These differences seem to result largely from variations in the simulated patterns of changes in key meteorological drivers, such as temperature and surface insolation. How isoprene nitrate chemistry is represented in the different modeling systems is an additional critical factor in the simulated O3 response to climate change.

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.

This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit greater fluctuations in the CMAQ cases than in the CALGRID cases, which lead to different placement of the urban ozone plumes. The CALGRID cases, which rely on the SAPRC97 chemical mechanism, exhibited a greater diurnal production/loss cycle of ozone concentrations per hour compared to either the RADM2 or CBIV chemical mechanisms in the CMAQ cases. These results demonstrate the need for specialized process field measurements to confirm whether we are modeling ozone with valid processes.

Given the stochastic nature of fire ignition and spread, a modeling approach is needed to estimate the range of fire effects possible on current and future landscapes. We are developing a nationwide Fire Scenario Builder (FSB) that creates self-consistent, spatially explicit U.S. prescribed and wildland fire scenarios for use in modeling both current and projected fire effects, including fire emissions. The FSB creates stochastic fire location and size scenarios that are consistent with known weather, vegetation, and land management controls on fire ignition and spread. At its core, the FSB is based on a coarsescale classification and quantification of fire regimes and tunable land management strategies. Fire regime attributes are created from reconstructed fire history, historical fire records, and potential natural vegetation. The FSB also utilizes weather and climate information from global climate model output. The climate projections used in this effort are those from the NCAR Climate Systems Model which contains the CCM3 atmospheric model at T42 resolution, but the FS B methodology is not limited to a particular model or resolution. The FSB utilizes in parallel known statistical relationships between climate, vegetation, and fire to create fire-ignition probabilities and a probability distribution of estimated fire sizes. The FSB is still under development, but we present initial results from forecasts for 19962000 and 2046 -2050 based on initial vegetation, lightning, and relative humidity relationships. Future work will utilize dynamical downscaling of the GCM output using the MM5 mesoscale model to increase spatial resolution and adapt the FSB to application at multiple spatial scales.