With harmful ozone concentrations tied to meteorological conditions, EPA investigates the U.S. air quality implications of a changing climate. Consequently, the 03 NAAQS are most often exceeded during summertime hot spells in places with large natural or anthropogenic precursor emissions (e.g., cities and suburban areas). Table 2 The average maximum or minimum temperature and/or changes in their spatial distribution and duration, leading to a change in reaction rate coefficients and the solubility of gases in cloud water solution;The frequency and pattern of cloud cover, leading to a change in reaction rates and rates of conversion of S02to acid deposition;The frequency and intensity of stagnation episodes or a change in the mixing layer, leading to more or less mixing of polluted air with background air;Background boundary layer concentrations of water vapor, hydrocarbons, NOx, and 03, leading to more or less dilution of polluted air in the boundary layer and altering the chemical transformation rates;

Abstract. The impact that changes in future climate, anthropogenic US emissions, background tropospheric composition, and land-use have on summertime regional US ozone and PM 2.5 concentrations is examined through a matrix of downscaled regional air quality simulations, where each set of simulations was conducted for five months of July climatology, using the Community Multi-scale Air Quality (CMAQ) model. Projected regional scale changes in meteorology due to climate change under the Intergovernmental Panel on Climate Change (IPCC) A2 scenario are derived through the downscaling of Parallel Climate Model (PCM) output with the MM5 meteorological model. Future chemical boundary conditions are obtained through downscaling of MOZART-2 (Model for Ozone and Related Chemical Tracers, version 2.4) global chemical model simulations based on the IPCC Special Report on Emissions Scenarios (SRES) A2 emissions scenario. Projected changes in US anthropogenic emissions are estimated using the EPA Economic Growth Analysis System (EGAS), and changes in land-use are projected using data from the Community Land Model (CLM) and the Spatially Explicit Regional Growth Model (SER-GOM). For July conditions, changes in chemical boundary conditions are found to have the largest impact (+5 ppbv) on average daily maximum 8-h (DM8H) ozone. Changes in US anthropogenic emissions are projected to increase average DM8H ozone by +3 ppbv. Land-use changes are projected to have a significant influence on regional air quality due to the impact these changes have on biogenic hydrocarbon emissions. When climate changes and land-use changes are conCorrespondence to: B. Lamb (blamb@wsu.edu) sidered simultaneously, the average DM8H ozone decreases due to a reduction in biogenic VOC emissions (−2.6 ppbv). Changes in average 24-h (A24-h) PM 2.5 concentrations are dominated by projected changes in anthropogenic emissions (+3 µg m −3 ), while changes in chemical boundary conditions have a negligible effect. On average, climate change reduces A24-h PM 2.5 concentrations by −0.9 µg m −3 , but this reduction is more than tripled in the Southeastern US due to increased precipitation and wet deposition.

[1] We report continuous whole canopy isoprene emission fluxes from a northern hardwood forest in Michigan for the 1999-2002 growing seasons. The eddy covariance fluxes of isoprene, CO 2 , latent heat, and sensible heat are presented along with an analysis of the seasonal and year-to-year variations. Measurements were made in collaboration with the AmeriFlux site located at the University of Michigan Biological Station (UMBS) and the Program for Research on Oxidants: PHotochemistry, Emissions, and Transport (PROPHET). In general, isoprene emissions increased throughout the day with increasing temperature and light levels, peaked at midafternoon, and declined to zero by night. There were significant variations from one 30-min period to the next, and from one day to the next. Average midday isoprene fluxes were 2.8, 3.2, and 2.9 mg C m À2 h À1 for 2000 through 2002, respectively. Insufficient data were available to include 1999. Last frost and full leaf out were significantly later in 2002 compared to the other years; however, total accumulated isoprene emissions for each year varied by less than 10%. Fully developed isoprene emissions occurred between 400 and 500 heating degree days, roughly half those required at other sites. Using long-term net ecosystem exchange measurements from the UMBS$Flux group, isoprene emissions represent between 1.7 to 3.1% of the net carbon uptake at this site. Observations for 2000-2002 were compared with the BEIS3 emission model. Estimates agree well with observations during the midsummer period, but BEIS3 overestimates observations during the spring onset of emissions and the fall decline in emissions. This work provides a unique long-term data set useful for verifying canopy scale models and to help us better understand the dynamics of biosphere-atmosphere exchange of isoprene.

Abstract. Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from 12 state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, US, August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within 1 d are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models, with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by fire radiative power (FRP)-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019, mainly over the transported smoke plumes, owing to the underestimated emissions on 7 August. In contrast, the surface smoke PM2.5 (sPM2.5) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM2.5. Overpredictions of sPM2.5 are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center's Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 3–8 August, the plume height became deeper, with a day-to-day range of about 2–9 km a.g.l. However, narrower ranges are found for all models, with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported smoke that is 1 d old. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated for by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.