Surface ozone (O3) pollution levels are strongly correlated with daytime surface temperatures, especially in highly polluted regions. This correlation is nonlinear and occurs through a variety of temperature-dependent mechanisms related to O3 precursor emissions, lifetimes, and reaction rates, making the reproduction of temperature sensitivities - and the projection of associated human health risks - a complex problem. Here we explore the summertime O3- temperature relationship in the United States and Europe using the chemical transport model GEOS-Chem. We remove the temperature dependence of several mechanisms most frequently cited as causes of the O3-temperature "climate penalty", including PAN decomposition, soil NOx emissions, biogenic volatile organic compound (VOC) emissions, and dry deposition. We quantify the contribution of each mechanism to the overall correlation between O3 and temperature both individually and collectively. Through this analysis we find that the thermal decomposition of PAN can explain, on average, 20 % of the overall O3-temperature correlation in the United States. The effect is weaker in Europe, explaining 9 % of the overall O3-temperature relationship. The temperature dependence of biogenic emissions contributes 3 % and 9 % of the total O3-temperature correlation in the United States and Europe on average, while temperaturedependent deposition (6 % and 1 %) and soil NOx emissions (10 % and 7 %) also contribute. Even considered collectively these mechanisms explain less than 46 % of the modeled O3- temperature correlation in the United States and 36 % in Europe. We use commonality analysis to demonstrate that covariance with other meteorological phenomena such as stagnancy and humidity can explain the bulk of the remainder of the O3-temperature correlation. Thus, we demonstrate that the statistical correlation between O3 and temperature alone may greatly overestimate the direct impacts of temperature on O3, with implications for the interpretation of policyrelevant metrics such as climate penalty.

An expected global increase in bioenergy-crop cultivation as an alternative to fossil fuels will have consequences on both global climate and local air quality through changes in biogenic emissions of volatile organic compounds (VOCs). While greenhouse gas emissions may be reduced through the substitution of next-generation bioenergy crops such as eucalyptus, giant reed, and switchgrass for fossil fuels, the choice of species has important ramifications for human health, potentially reducing the benefits of conversion due to increases in ozone (O3) and fine particulate matter (PM2.5) levels as a result of large changes in biogenic emissions. Using the Community Earth System Model we simulate the conversion of marginal and underutilized croplands worldwide to bioenergy crops under varying future anthropogenic emissions scenarios. A conservative global replacement using high VOC-emitting crop profiles leads to modeled population-weighted O3 increases of 5-27 ppb in India, 1-9 ppb in China, and 1-6 ppb in the United States, with peak PM2.5 increases of up to 2 μg m^-3. We present a metric for the regional evaluation of candidate bioenergy crops, as well as results for the application of this metric to four representative emissions profiles using four replacement scales (10-100% maximum estimated available land). Finally, we assess the total health and climate impacts of biogenic emissions, finding that the negative consequences of using high-emitting crops could exceed 50% of the positive benefits of reduced fossil fuel emissions in value.

The intensity and frequency of wildfires in California (CA) have increased in recent years, causing significant damage to human health and property. In October 2007, a number of small fire events, collectively referred to as the Witch Creek Fire or Witch Fire started in Southern CA and intensified under strong Santa Ana winds. As a test of current mesoscale modeling capabilities, we use the Weather Research and Forecasting (WRF) model to simulate the 2007 wildfire event in terms of meteorological conditions. The main objectives of the present study are to investigate the impact of horizontal grid resolution and planetary boundary layer (PBL) scheme on the model simulation of meteorological conditions associated with a Mega fire. We evaluate the predictive capability of the WRF model to simulate key meteorological and fire-weather forecast parameters such as wind, moisture, and temperature. Results of this study suggest that more accurate predictions of temperature and wind speed relevant for better prediction of wildfire spread can be achieved by downscaling regional numerical weather prediction products to 1 km resolution. Furthermore, accurate prediction of near-surface conditions depends on the choice of the planetary boundary layer parameterization. The MYNN parameterization yields more accurate prediction as compared to the YSU parameterization. WRF simulations at 1 km resolution result in better predictions of temperature and wind speed than relative humidity during the 2007 Witch Fire. In summary, the MYNN PBL parameterization scheme with finer grid resolution simulations improves the prediction of near-surface meteorological conditions during a wildfire event.

The Goddard Earth Observing System with chemistry (GEOS-Chem) model has been updated with the Statewide Air Pollution Research Center version 11 (SAPRC-11) aromatics chemical mechanism, with the purpose of evaluating global and regional effects of the most abundant aromatics (benzene, toluene, xylenes) on the chemical species important for tropospheric oxidation capacity. The model evaluation based on surface and aircraft observations indicates good agreement for aromatics and ozone. A comparison between scenarios in GEOS-Chem with simplified aromatic chemistry (as in the standard setup, with no ozone formation from related peroxy radicals or recycling of NO_x) and with the SAPRC-11 scheme reveals relatively slight changes in ozone, the hydroxyl radical, and nitrogen oxides on a global mean basis (1 %-4 %), although remarkable regional differences (5 %-20 %) exist near the source regions. NO _x decreases over the source regions and increases in the remote troposphere, due mainly to more efficient transport of peroxyacetyl nitrate (PAN), which is increased with the SAPRC aromatic chemistry. Model ozone mixing ratios with the updated aromatic chemistry increase by up to 5 ppb (more than 10 %), especially in industrially polluted regions. The ozone change is partly due to the direct influence of aromatic oxidation products on ozone production rates, and in part to the altered spatial distribution of NOx that enhances the tropospheric ozone production efficiency. Improved representation of aromatics is important to simulate the tropospheric oxidation.

We conduct a case study of observed and simulated maximum daily 8-h average (MDA8) ozone (O3) in three US cities for summers during 1996–2005. The purpose of this study is to evaluate the ability of a high resolution atmospheric chemistry model to reproduce observed relationships between meteorology and high or extreme O3. We employ regional coupled chemistry-transport model simulations to make three types of comparisons between simulated and observational data, comparing (1) tails of the O3 response variable, (2) distributions of meteorological predictor variables, and (3) sensitivities of high and extreme O3 to meteorological predictors. This last comparison is made using two methods: quantile regression, for the 0.95 quantile of O3, and tail dependence optimization, which is used to investigate even higher O3 extremes. Across all three locations, we find substantial differences between simulations and observational data in both meteorology and meteorological sensitivities of high and extreme O3.